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Give an example of a research question when you need to perform clustering (psechometric field)
How can we group test-takers based on their performance on a set of psychometric tests and demographic information, in order to better understand different cognitive and non-cognitive traits?
 

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Give an example of a research question when you need to perform clustering (psechometric field)
Write an answer for statistics test:
A school manager noticed that the absence rate of students notably is growing in the school. Absence is a situation in which a student prefer not to attend a class and miss it. To identify what factors may lead to growth of absence rate of student in this school, he invited a researcher to conduct a study. The researcher found three potential factors that may provoke a student to attend or miss a class. These factors were gender of students, distance between the school and the living place, interest to teacher, and interest to class subject.
a) What type of regression analysis best can help the researcher to test role of these factors in provoking a student to attend or miss a class?
 

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What are the distinct patterns of customer purchasing behavior for a retail store based on their shopping history and demographic information?
Write an answer for statistics test:
A school manager noticed that the absence rate of students notably is growing in the school. Absence is a situation in which a student prefer not to attend a class and miss it. To identify what factors may lead to growth of absence rate of student in this school, he invited a researcher to conduct a study. The researcher found three potential factors that may provoke a student to attend or miss a class. These factors were gender of students, distance between the school and the living place, interest to teacher, and interest to class subject.
a) What type of regression analysis best can help the researcher to test role of these factors in provoking a student to attend or miss a class?
 

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Write an answer for statistics test:
A school manager noticed that the absence rate of students notably is growing in the school. Absence is a situation in which a student prefer not to attend a class and miss it. To identify what factors may lead to growth of absence rate of student in this school, he invited a researcher to conduct a study. The researcher found three potential factors that may provoke a student to attend or miss a class. These factors were gender of students, distance between the school and the living place, interest to teacher, and interest to class subject.
a) What type of regression analysis best can help the researcher to test role of these factors in provoking a student to attend or miss a class?
Multiple linear regression would be the best type of analysis to test the role of these factors in provoking a student to attend or miss a class. This is because multiple linear regression allows the researcher to examine the relationship between a continuous dependent variable (such as absence rate) and several independent variables (such as gender, distance, interest to teacher and interest to class subject) simultaneously. By analyzing the data using multiple linear regression, the researcher can estimate the effect of each independent variable on absence rate while controlling for the other variables in the model. This type of analysis can provide valuable information about which factors are most strongly associated with absence rate and can help the school manager make informed decisions about how to address this issue.
 

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Multiple linear regression would be the best type of analysis to test the role of these factors in provoking a student to attend or miss a class. This is because multiple linear regression allows the researcher to examine the relationship between a continuous dependent variable (such as absence rate) and several independent variables (such as gender, distance, interest to teacher and interest to class subject) simultaneously. By analyzing the data using multiple linear regression, the researcher can estimate the effect of each independent variable on absence rate while controlling for the other variables in the model. This type of analysis can provide valuable information about which factors are most strongly associated with absence rate and can help the school manager make informed decisions about how to address this issue.
Write an answer for statistics test:
A school manager noticed that the absence rate of students notably is growing in the school. Absence is a situation in which a student prefer not to attend a class and miss it. To identify what factors may lead to growth of absence rate of student in this school, he invited a researcher to conduct a study. The researcher found three potential factors that may provoke a student to attend or miss a class. These factors were gender of students, distance between the school and the living place, interest to teacher, and interest to class subject.
a) What type of regression analysis best can help the researcher to test role of these factors in provoking a student to attend or miss a class?
b) Provide at least a reason to support your answer?
c) Identify and list all IVs and DVs in this question.
 

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Write an answer for statistics test:
A school manager noticed that the absence rate of students notably is growing in the school. Absence is a situation in which a student prefer not to attend a class and miss it. To identify what factors may lead to growth of absence rate of student in this school, he invited a researcher to conduct a study. The researcher found three potential factors that may provoke a student to attend or miss a class. These factors were gender of students, distance between the school and the living place, interest to teacher, and interest to class subject.
a) What type of regression analysis best can help the researcher to test role of these factors in provoking a student to attend or miss a class?
b) Provide at least a reason to support your answer?
c) Identify and list all IVs and DVs in this question.
a) The type of regression analysis that best suits this research question is multiple linear regression.

b) Multiple linear regression is the most appropriate type of analysis in this research scenario as it allows the researcher to examine the relationships between the absence rate (dependent variable) and multiple independent variables (gender, distance, interest to teacher, and interest to class subject) simultaneously. Multiple linear regression can help to identify the most significant predictors of the absence rate while taking into account the potential influence of other variables.

c)
IVs:
1. Gender of students (categorical)
2. Distance between the school and the living place (continuous)
3. Interest to teacher (continuous)
4. Interest to class subject (continuous)

DV:
1. Absence rate of students (continuous)
 

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a) The type of regression analysis that best suits this research question is multiple linear regression.

b) Multiple linear regression is the most appropriate type of analysis in this research scenario as it allows the researcher to examine the relationships between the absence rate (dependent variable) and multiple independent variables (gender, distance, interest to teacher, and interest to class subject) simultaneously. Multiple linear regression can help to identify the most significant predictors of the absence rate while taking into account the potential influence of other variables.

c)
IVs:
1. Gender of students (categorical)
2. Distance between the school and the living place (continuous)
3. Interest to teacher (continuous)
4. Interest to class subject (continuous)

DV:
1. Absence rate of students (continuous)
1679568467819.png
What percentage of initial data variance is explained by PC2?
 

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Посмотреть вложение 132037 What percentage of initial data variance is explained by PC2?
Without the specific data and results of a principal component analysis or PCA, it is not possible to give an exact answer to this question. However, in a PCA, each principal component (PC) explains a portion of the total variation in the data. The proportion of variance explained by each PC is given by its eigenvalue, and the total variance explained by all PCs add up to 100%.

Therefore, the percentage of initial data variance explained by PC2 would be the eigenvalue for PC2 divided by the total sum of all the eigenvalues, multiplied by 100%.
 

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Without the specific data and results of a principal component analysis or PCA, it is not possible to give an exact answer to this question. However, in a PCA, each principal component (PC) explains a portion of the total variation in the data. The proportion of variance explained by each PC is given by its eigenvalue, and the total variance explained by all PCs add up to 100%.

Therefore, the percentage of initial data variance explained by PC2 would be the eigenvalue for PC2 divided by the total sum of all the eigenvalues, multiplied by 100%.
Write an answer for statistics test: You explore the structure of the instrument measuring intrinsic and extrinsic motivation with Exploratory Factor Analysis. What type of rotation should you use in case you want to extract two latent factors? Write the type of rotation and explain your choice.
 

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Write an answer for statistics test: You explore the structure of the instrument measuring intrinsic and extrinsic motivation with Exploratory Factor Analysis. What type of rotation should you use in case you want to extract two latent factors? Write the type of rotation and explain your choice.
When exploring the structure of an instrument measuring intrinsic and extrinsic motivation with exploratory factor analysis and wanting to extract two latent factors, the recommended type of rotation to use is the orthogonal rotation method called the Varimax rotation.

The Varimax rotation is designed to maximize the variance of the square of the loadings of the items on each factor, producing a clear differentiation between the items loading heavily on each individual factor while minimizing the variance shared between the factors. It can make interpretation and understanding of the resulting factor structure easier since factor loadings on each factor are distinct and less shared by other factors.

Using an orthogonal rotation method such as Varimax rotation, also allows easier interpretation of the factor structure since the factors obtained are not correlated with each other, which can be helpful in the case where distinct factors are being sought.

Overall, the Varimax rotation would be an appropriate type of rotation since it is less complex and less affected by factor correlations, making it easier to interpret and more useful for extracting multiple distinct factors.
 

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When exploring the structure of an instrument measuring intrinsic and extrinsic motivation with exploratory factor analysis and wanting to extract two latent factors, the recommended type of rotation to use is the orthogonal rotation method called the Varimax rotation.

The Varimax rotation is designed to maximize the variance of the square of the loadings of the items on each factor, producing a clear differentiation between the items loading heavily on each individual factor while minimizing the variance shared between the factors. It can make interpretation and understanding of the resulting factor structure easier since factor loadings on each factor are distinct and less shared by other factors.

Using an orthogonal rotation method such as Varimax rotation, also allows easier interpretation of the factor structure since the factors obtained are not correlated with each other, which can be helpful in the case where distinct factors are being sought.

Overall, the Varimax rotation would be an appropriate type of rotation since it is less complex and less affected by factor correlations, making it easier to interpret and more useful for extracting multiple distinct factors.
Please take a small block of a discipline you like. It's important that this block would be a singular topic, for example, so it would have some logical boundaries. Write down a) learning outcomes that should be tested within this block b) leveles of taxonomy that should be tested concerning these LO. Develop a test item for measuring each LO. Try to develop items of different forms and explain why each form was chosen. Please use multiple choice form at least for some of the LO. While developing multiple choice items please explain your choice of the distractors. I don't expect you to develop many items but it's important that you would develop high quality items. Please use the materials of our lectures.

Criteria for LO

A
The objective is either an educational objective or an instructional
objective, not a global objective. (put + or -, add a comment if necessary)
B
The objective specifies an actual process or skill (a verb) that students
are to carry out after instruction. The objective contains a precise, specific,
observable verb.
C
The objective specifies some targeted content (a noun) for students to
learn. The content represents an important aspect of learning within
the discipline, not a trivial aspect.
D
The objective is stated in terms of what students are expected to learn
from instruction—not in terms of what the teacher will learn, or in terms of
the activities in which students will engage.
E
The objective begins with a verb.
F
The objective lends itself to assessment using paper-and-pencil
testing.

G
The objective describes a probable learning outcome for a lesson.

H
The objective is stated as an observable student behavior.


Criteria for Evaluating Sets of Matching Items

A
This is an appropriate item type to use for the intended objective.
B
All the content presented in the set of matching items is correct.
C
The reading level of the set of matching items is appropriate for the students.
D
The material in the two lists is homogenous.
E
The number of responses and premises is unequal. More (or fewer) responses
than premises are included. Alternatively, the directions state that some of the
responses could be used more than one time.
F
The responses are brief and are on the right-hand side.
G
There are 4 to 10 premises listed.
H
All the premises and responses are grammatically consistent.
I
The directions indicate the basis for matching.
J
The directions describe the type of response the student is expected to make
(e.g., “Draw a line to match _ with _.” or “On the line to the left of each ___ listed
in column A, write the letter from column B that identifies _ __.”).
K
The directions indicate the number of times that each response may be used
(e.g., “Each __ in column B may be used no more than once” or “Each __ in
column B may be used once, more than once, or not at all.”).
L
There is one correct match for each premise.
M
The responses are in a logical order (i.e., words in alphabetical order, numbers in
sequence).
N
All the premises and responses for the item appear on a single page.

Criteria for Evaluating True-False/Binary-Choice Items

A
This is an appropriate item type to use for the intended objective.
B
The statement can be judged clearly true or false, right or wrong, fact
or opinion, etc.
C
The item is not trivial—it reflects important learning.
D
The reading level of the item is appropriate for the students.
E
The item does not contain any specific determiners (e.g., all,
usually, most, generally, never, sometimes, all, none, may).
F
The item is stated positively, not negatively.
G
The item is stated in simple, clear language.
H
If the item is an opinion statement, the opinion was attributed to
some source.
I
The item contains a single concept/idea.
A
Clear directions are provided for this section of the test that focus
students on what to do, how to respond, and where to place their
answers.
B
There are approximately equal numbers of true and false items.
C
A detectable pattern of answers (e.g., T, F, T, F) has been avoided.
D
true and false items are approximately equal in length (i.e., the
tendency to make long statements true and short statements false has
been avoided).
E
The true-false items are formatted so that the T’s and F’s are lined
in columns to make it easier for students to respond to each item.

Criteria for Evaluating Multiple-Choice Items

A
This is an appropriate item type to use for the intended objective.
B
The content presented in the item is correct. There is only one correct or
clearly best answer for the item.
C
The reading level of the item is appropriate for the students.
D
The stem sets the problem clearly, presenting a meaningful problem (i.e.,
you can understand what is being asked without having to read the options).
E
The stem is free of irrelevant material. There are no unneeded words.
F
Repeated words are included in the stem, rather than in each option.
G
The stem is stated in positive terms (if possible). If used, negative wording
in the stem has special emphasis (i.e., underlined, in bold, or caps).
H
The options are all grammatically consistent with the item stem. There are
no grammatical clues to the answer.
I
The options are similar in length and form.
J
The options are brief and free of unnecessary words.
K
The item is free of verbal clues that could cue the right answer.
L
All the distracters are plausible to low achievers (i.e., there are no “throw-
away” options).
M
Numerical options are in numerical order.
N
“All of the above” is never used as an option.
O
If “None of the above” is used, it is used sparingly and only when
measurement of the intended objective requires it.
A
Clear directions are provided for this section of the test that focus students on what to do,
how to respond, and where to place their answers.
B
Each option for an item appears on a separate line beneath the stem.
C
Capital letters are used to identify each option rather than lower-case letters.
D
Each item is properly formatted, displaying correct punctuation and capitalization in the
stem and in each option.
E
The answer key is balanced so that the correct answer appears in alternative positions a
nearly equal number of times but in random order.
F
A detectable pattern of correct answers (e.g., A, B, C, D, A, B, C, D, etc.) has been
avoided.

Criteria for Evaluating Sequence Items

A
The elements are homogenous in different aspects (grammatical forms, reading level, style)
B
The principle of sequence is clearly stated and undoubtful (and only one)
C
There is a clear instruction how to perform an item (e.g. drag and drop, give numbers, write down the numbers in proper order)
D
There is a distinctive place for answers
 

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Please take a small block of a discipline you like. It's important that this block would be a singular topic, for example, so it would have some logical boundaries. Write down a) learning outcomes that should be tested within this block b) leveles of taxonomy that should be tested concerning these LO. Develop a test item for measuring each LO. Try to develop items of different forms and explain why each form was chosen. Please use multiple choice form at least for some of the LO. While developing multiple choice items please explain your choice of the distractors. I don't expect you to develop many items but it's important that you would develop high quality items. Please use the materials of our lectures.

Criteria for LO

A
The objective is either an educational objective or an instructional
objective, not a global objective. (put + or -, add a comment if necessary)
B
The objective specifies an actual process or skill (a verb) that students
are to carry out after instruction. The objective contains a precise, specific,
observable verb.
C
The objective specifies some targeted content (a noun) for students to
learn. The content represents an important aspect of learning within
the discipline, not a trivial aspect.
D
The objective is stated in terms of what students are expected to learn
from instruction—not in terms of what the teacher will learn, or in terms of
the activities in which students will engage.
E
The objective begins with a verb.
F
The objective lends itself to assessment using paper-and-pencil
testing.

G
The objective describes a probable learning outcome for a lesson.

H
The objective is stated as an observable student behavior.


Criteria for Evaluating Sets of Matching Items

A
This is an appropriate item type to use for the intended objective.
B
All the content presented in the set of matching items is correct.
C
The reading level of the set of matching items is appropriate for the students.
D
The material in the two lists is homogenous.
E
The number of responses and premises is unequal. More (or fewer) responses
than premises are included. Alternatively, the directions state that some of the
responses could be used more than one time.
F
The responses are brief and are on the right-hand side.
G
There are 4 to 10 premises listed.
H
All the premises and responses are grammatically consistent.
I
The directions indicate the basis for matching.
J
The directions describe the type of response the student is expected to make
(e.g., “Draw a line to match _ with .” or “On the line to the left of each __ listed
in column A, write the letter from column B that identifies _ __.”).
K
The directions indicate the number of times that each response may be used
(e.g., “Each __ in column B may be used no more than once” or “Each __ in
column B may be used once, more than once, or not at all.”).
L
There is one correct match for each premise.
M
The responses are in a logical order (i.e., words in alphabetical order, numbers in
sequence).
N
All the premises and responses for the item appear on a single page.

Criteria for Evaluating True-False/Binary-Choice Items

A
This is an appropriate item type to use for the intended objective.
B
The statement can be judged clearly true or false, right or wrong, fact
or opinion, etc.
C
The item is not trivial—it reflects important learning.
D
The reading level of the item is appropriate for the students.
E
The item does not contain any specific determiners (e.g., all,
usually, most, generally, never, sometimes, all, none, may).
F
The item is stated positively, not negatively.
G
The item is stated in simple, clear language.
H
If the item is an opinion statement, the opinion was attributed to
some source.
I
The item contains a single concept/idea.
A
Clear directions are provided for this section of the test that focus
students on what to do, how to respond, and where to place their
answers.
B
There are approximately equal numbers of true and false items.
C
A detectable pattern of answers (e.g., T, F, T, F) has been avoided.
D
true and false items are approximately equal in length (i.e., the
tendency to make long statements true and short statements false has
been avoided).
E
The true-false items are formatted so that the T’s and F’s are lined
in columns to make it easier for students to respond to each item.

Criteria for Evaluating Multiple-Choice Items

A
This is an appropriate item type to use for the intended objective.
B
The content presented in the item is correct. There is only one correct or
clearly best answer for the item.
C
The reading level of the item is appropriate for the students.
D
The stem sets the problem clearly, presenting a meaningful problem (i.e.,
you can understand what is being asked without having to read the options).
E
The stem is free of irrelevant material. There are no unneeded words.
F
Repeated words are included in the stem, rather than in each option.
G
The stem is stated in positive terms (if possible). If used, negative wording
in the stem has special emphasis (i.e., underlined, in bold, or caps).
H
The options are all grammatically consistent with the item stem. There are
no grammatical clues to the answer.
I
The options are similar in length and form.
J
The options are brief and free of unnecessary words.
K
The item is free of verbal clues that could cue the right answer.
L
All the distracters are plausible to low achievers (i.e., there are no “throw-
away” options).
M
Numerical options are in numerical order.
N
“All of the above” is never used as an option.
O
If “None of the above” is used, it is used sparingly and only when
measurement of the intended objective requires it.
A
Clear directions are provided for this section of the test that focus students on what to do,
how to respond, and where to place their answers.
B
Each option for an item appears on a separate line beneath the stem.
C
Capital letters are used to identify each option rather than lower-case letters.
D
Each item is properly formatted, displaying correct punctuation and capitalization in the
stem and in each option.
E
The answer key is balanced so that the correct answer appears in alternative positions a
nearly equal number of times but in random order.
F
A detectable pattern of correct answers (e.g., A, B, C, D, A, B, C, D, etc.) has been
avoided.

Criteria for Evaluating Sequence Items

A
The elements are homogenous in different aspects (grammatical forms, reading level, style)
B
The principle of sequence is clearly stated and undoubtful (and only one)
C
There is a clear instruction how to perform an item (e.g. drag and drop, give numbers, write down the numbers in proper order)
D
There is a distinctive place for answers
The discipline: Biology

Topic: The Cell Theory

Learning Outcomes to be Tested:

1. Identify the three components of the cell theory.
2. Understand the historical developments that led to the formation of the cell theory.
3. Recognize the characteristics of living organisms that are explained by the cell theory.

Levels of Taxonomy:

1. Remembering
2. Understanding
3. Analyzing

Test Items:

1. Multiple Choice: The three components of the cell theory are:
a. Cells are the smallest unit of life, all living things are made up of cells, and cells can only arise from pre-existing cells.
b. Cells can only arise from pre-existing cells, all living things are made up of cells, and cells are the smallest unit of life.
c. All living things are made up of cells, cells can only arise from pre-existing cells, and cells have a membrane-bound nucleus.
d. Cells are the smallest unit of life, all living things are made up of cells, and cells have a membrane-bound nucleus.
(Answer: b)
Explanation of Distractors: Distractor A is incorrect because it omits the second component of the cell theory. Distractor C is incorrect because it adds an incorrect third component to the cell theory.
Form of Item: Multiple choice was chosen for this item because it allows for precise testing of the learning outcome.
Level of Taxonomy: Remembering

2. True-False: The cell theory was developed in the 19th century.
(Answer: True)
Explanation of Item: This item tests the student's understanding of the historical developments that led to the formation of the cell theory. The learning outcome indicates an understanding of historical events, which is best tested with a true-false question.
Level of Taxonomy: Understanding

3. Matching: Match the characteristic to the component of the cell theory that it explains:
(A) All living things are made up of cells. (1) Cells are the smallest unit of life.
(B) Viruses are not composed of cells. (2) All cells arise from pre-existing cells.
(C) Mitosis is a process by which cells divide. (3) Cells are the basic unit of structure and function in living things.
(Answer: A3, B1, C2)
Explanation of Distractors: None needed, as there is only one correct match for each premise.
Form of Item: Matching was chosen because it requires the student to analyze the relationships between components of the cell theory and characteristics of living organisms.
Level of Taxonomy: Analyzing

4. Ordering: Place the following events in the order they occurred, leading to the development of the cell theory:
_____ a. Discovery of the nucleus
_____ b. Observation of cells under the microscope
_____ c. Development of the germ theory of disease
(Answer: b, a, c)
Explanation of Item: This item tests the student's ability to analyze the historical developments that led to the formation of the cell theory. Ordering was chosen because it requires the student to sequence events chronologically.
Level of Taxonomy: Analyzing.

5. Short Answer: State which components of the cell theory were present in the work of Robert Hooke.
(Answer: The component that states that cells are the basic unit of structure and function in living things.)
Explanation of Item: This items tests the student's ability to recall historical events and their relation to the components of the cell theory. Short answer was chosen because it allows for a brief and specific response.
Level of Taxonomy: Remembering.
 

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The discipline: Biology

Topic: The Cell Theory

Learning Outcomes to be Tested:

1. Identify the three components of the cell theory.
2. Understand the historical developments that led to the formation of the cell theory.
3. Recognize the characteristics of living organisms that are explained by the cell theory.

Levels of Taxonomy:

1. Remembering
2. Understanding
3. Analyzing

Test Items:

1. Multiple Choice: The three components of the cell theory are:
a. Cells are the smallest unit of life, all living things are made up of cells, and cells can only arise from pre-existing cells.
b. Cells can only arise from pre-existing cells, all living things are made up of cells, and cells are the smallest unit of life.
c. All living things are made up of cells, cells can only arise from pre-existing cells, and cells have a membrane-bound nucleus.
d. Cells are the smallest unit of life, all living things are made up of cells, and cells have a membrane-bound nucleus.
(Answer: b)
Explanation of Distractors: Distractor A is incorrect because it omits the second component of the cell theory. Distractor C is incorrect because it adds an incorrect third component to the cell theory.
Form of Item: Multiple choice was chosen for this item because it allows for precise testing of the learning outcome.
Level of Taxonomy: Remembering

2. True-False: The cell theory was developed in the 19th century.
(Answer: True)
Explanation of Item: This item tests the student's understanding of the historical developments that led to the formation of the cell theory. The learning outcome indicates an understanding of historical events, which is best tested with a true-false question.
Level of Taxonomy: Understanding

3. Matching: Match the characteristic to the component of the cell theory that it explains:
(A) All living things are made up of cells. (1) Cells are the smallest unit of life.
(B) Viruses are not composed of cells. (2) All cells arise from pre-existing cells.
(C) Mitosis is a process by which cells divide. (3) Cells are the basic unit of structure and function in living things.
(Answer: A3, B1, C2)
Explanation of Distractors: None needed, as there is only one correct match for each premise.
Form of Item: Matching was chosen because it requires the student to analyze the relationships between components of the cell theory and characteristics of living organisms.
Level of Taxonomy: Analyzing

4. Ordering: Place the following events in the order they occurred, leading to the development of the cell theory:
_____ a. Discovery of the nucleus
_____ b. Observation of cells under the microscope
_____ c. Development of the germ theory of disease
(Answer: b, a, c)
Explanation of Item: This item tests the student's ability to analyze the historical developments that led to the formation of the cell theory. Ordering was chosen because it requires the student to sequence events chronologically.
Level of Taxonomy: Analyzing.

5. Short Answer: State which components of the cell theory were present in the work of Robert Hooke.
(Answer: The component that states that cells are the basic unit of structure and function in living things.)
Explanation of Item: This items tests the student's ability to recall historical events and their relation to the components of the cell theory. Short answer was chosen because it allows for a brief and specific response.
Level of Taxonomy: Remembering.
write code in R to do analyze iPIPS Russian version:
-correlation coefficients or chi-square test of independence (any);
-ANOVA OR T-test;
-Linear regression analysis OR Logistic regression analysis;
-Exploratory factor analysis OR Principal component analysis OR Cluster analysis (k-means).
 

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write code in R to do:
-correlation coefficients or chi-square test of independence (any);
-ANOVA OR T-test;
-Linear regression analysis OR Logistic regression analysis;
-Exploratory factor analysis OR Principal component analysis OR Cluster analysis (k-means).
Correlation coefficients:

# create two variables
x <- c(1, 2, 3, 4, 5)
y <- c(5, 4, 3, 2, 1)

# calculate the correlation coefficient
cor(x, y)


Chi-square test of independence:

# create a contingency table
data <- matrix(c(10, 20, 30, 40), nrow = 2)
colnames(data) <- c("Group A", "Group B")
rownames(data) <- c("Male", "Female")

# perform chi-square test
chisq.test(data)


One-way ANOVA:

# create three groups of data
a <- c(20, 25, 30, 35, 40)
b <- c(15, 20, 25, 30, 35)
c <- c(10, 15, 20, 25, 30)

# perform ANOVA
anova(lm(c(a, b, c) ~ rep(c("a", "b", "c"), each = 5)))


Linear regression analysis:

# create two variables
x <- c(1, 2, 3, 4, 5)
y <- c(5, 4, 3, 2, 1)

# perform linear regression
lm(y ~ x)


Logistic regression analysis:

# create binary response variable and predictor
response <- c("Yes", "No", "No", "Yes", "No", "No", "Yes", "Yes")
predictor <- c(1, 2, 3, 4, 5, 6, 7, 8)

# perform logistic regression
glm(response ~ predictor, family = binomial)


Exploratory factor analysis:

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50), z = rnorm(50))

# perform exploratory factor analysis
library("psych")
fa(data, nfactors = 2)


Principal component analysis:

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50), z = rnorm(50))

# perform principal component analysis
prcomp(data)


Cluster analysis (k-means):

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50))

# perform cluster analysis
kmeans(data, centers = 2)
 

wtfumean

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write code in R to do:
-correlation coefficients or chi-square test of independence (any);
-ANOVA OR T-test;
-Linear regression analysis OR Logistic regression analysis;
-Exploratory factor analysis OR Principal component analysis OR Cluster analysis (k-means).


setwd("C://Users//lunin//Downloads")
data <- import("iPIPS_2018-2019 - Copy.xlsx")
 

wtfumean

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Correlation coefficients:

# create two variables
x <- c(1, 2, 3, 4, 5)
y <- c(5, 4, 3, 2, 1)

# calculate the correlation coefficient
cor(x, y)


Chi-square test of independence:

# create a contingency table
data <- matrix(c(10, 20, 30, 40), nrow = 2)
colnames(data) <- c("Group A", "Group B")
rownames(data) <- c("Male", "Female")

# perform chi-square test
chisq.test(data)


One-way ANOVA:

# create three groups of data
a <- c(20, 25, 30, 35, 40)
b <- c(15, 20, 25, 30, 35)
c <- c(10, 15, 20, 25, 30)

# perform ANOVA
anova(lm(c(a, b, c) ~ rep(c("a", "b", "c"), each = 5)))


Linear regression analysis:

# create two variables
x <- c(1, 2, 3, 4, 5)
y <- c(5, 4, 3, 2, 1)

# perform linear regression
lm(y ~ x)


Logistic regression analysis:

# create binary response variable and predictor
response <- c("Yes", "No", "No", "Yes", "No", "No", "Yes", "Yes")
predictor <- c(1, 2, 3, 4, 5, 6, 7, 8)

# perform logistic regression
glm(response ~ predictor, family = binomial)


Exploratory factor analysis:

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50), z = rnorm(50))

# perform exploratory factor analysis
library("psych")
fa(data, nfactors = 2)


Principal component analysis:

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50), z = rnorm(50))

# perform principal component analysis
prcomp(data)


Cluster analysis (k-means):

# create a data set
data <- data.frame(x = rnorm(50), y = rnorm(50))

# perform cluster analysis
kmeans(data, centers = 2)
write code in R to do:
-correlation coefficients or chi-square test of independence (any);
-ANOVA OR T-test;
-Linear regression analysis OR Logistic regression analysis;
-Exploratory factor analysis OR Principal component analysis OR Cluster analysis (k-means).


setwd("C://Users//lunin//Downloads")
data <- import("iPIPS_2018-2019 - Copy.xlsx")
 

Garant [BOT]

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Статус
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15.11.2021
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Репутация
297
write code in R to do:
-correlation coefficients or chi-square test of independence (any);
-ANOVA OR T-test;
-Linear regression analysis OR Logistic regression analysis;
-Exploratory factor analysis OR Principal component analysis OR Cluster analysis (k-means).


setwd("C://Users//lunin//Downloads")
data <- import("iPIPS_2018-2019 - Copy.xlsx")
Correlation coefficients:

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# calculate the correlation coefficient
cor(x, y)


Chi-square test of independence:

# create a contingency table from the data
table <- table(data$Group, data$Response)

# perform chi-square test
chisq.test(table)


One-way ANOVA:

# select a variable and group from the data
variable <- data$Variable
group <- data$Group

# perform ANOVA
anova(lm(variable ~ group))


T-test:

# select two groups from the data
group1 <- data$Group1
group2 <- data$Group2

# perform t-test
t.test(group1, group2)


Linear regression analysis:

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# perform linear regression
lm(y ~ x)


Logistic regression analysis:

# select binary response variable and predictor from the data
response <- as.factor(data$Response)
predictor <- data$Predictor

# perform logistic regression
glm(response ~ predictor, family = binomial)


Exploratory factor analysis:

# select a subset of variables from the data
subset <- data[, c(1, 2, 3)]

# perform exploratory factor analysis
library("psych")
fa(subset, nfactors = 2)


Principal component analysis:

# select a subset of variables from the data
subset <- data[, c(1, 2, 3)]

# perform principal component analysis
prcomp(subset)


Cluster analysis (k-means):

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# perform cluster analysis
kmeans(data.frame(x, y), centers = 2)
 

wtfumean

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Correlation coefficients:

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# calculate the correlation coefficient
cor(x, y)


Chi-square test of independence:

# create a contingency table from the data
table <- table(data$Group, data$Response)

# perform chi-square test
chisq.test(table)


One-way ANOVA:

# select a variable and group from the data
variable <- data$Variable
group <- data$Group

# perform ANOVA
anova(lm(variable ~ group))


T-test:

# select two groups from the data
group1 <- data$Group1
group2 <- data$Group2

# perform t-test
t.test(group1, group2)


Linear regression analysis:

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# perform linear regression
lm(y ~ x)


Logistic regression analysis:

# select binary response variable and predictor from the data
response <- as.factor(data$Response)
predictor <- data$Predictor

# perform logistic regression
glm(response ~ predictor, family = binomial)


Exploratory factor analysis:

# select a subset of variables from the data
subset <- data[, c(1, 2, 3)]

# perform exploratory factor analysis
library("psych")
fa(subset, nfactors = 2)


Principal component analysis:

# select a subset of variables from the data
subset <- data[, c(1, 2, 3)]

# perform principal component analysis
prcomp(subset)


Cluster analysis (k-means):

# select two variables from the data
x <- data$Variable1
y <- data$Variable2

# perform cluster analysis
kmeans(data.frame(x, y), centers = 2)
Какие исследовательские вопросы можно задать к этим данным и что мы можем исследовать с помощью статиститеского анализа корреляции? https://docs.google.com/spreadsheets/d/1iFkPNljiFdZ_Z1hVmq6YuYmiqFeLyHbd/edit?rtpof=true&sd=true
 

Garant [BOT]

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Какие исследовательские вопросы можно задать к этим данным и что мы можем исследовать с помощью статиститеского анализа корреляции? https://docs.google.com/spreadsheets/d/1iFkPNljiFdZ_Z1hVmq6YuYmiqFeLyHbd/edit?rtpof=true&sd=true
Возможные исследовательские вопросы для этих данных:

1. Существует ли связь между двумя переменными (например, доход и уровень образования)?
2. Какова сила связи между этими переменными?
3. Какие значения переменных наиболее часто встречаются (например, есть ли некоторые значения переменных, которые наиболее популярны)?

С помощью статистического анализа корреляции можно исследовать связь между двумя переменными. Это позволяет оценить силу и направление связи между переменными. Если связь есть, то можно использовать это знание для прогнозирования значений одной переменной на основе значений другой переменной. Кроме того, можно использовать корреляционный анализ для выявления выбросов и аномальных значений.
 

wtfumean

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Статус
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Регистрация
14.04.2021
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226
Репутация
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Возможные исследовательские вопросы для этих данных:

1. Существует ли связь между двумя переменными (например, доход и уровень образования)?
2. Какова сила связи между этими переменными?
3. Какие значения переменных наиболее часто встречаются (например, есть ли некоторые значения переменных, которые наиболее популярны)?

С помощью статистического анализа корреляции можно исследовать связь между двумя переменными. Это позволяет оценить силу и направление связи между переменными. Если связь есть, то можно использовать это знание для прогнозирования значений одной переменной на основе значений другой переменной. Кроме того, можно использовать корреляционный анализ для выявления выбросов и аномальных значений.
Formulate a question formulation of a research problem and formulation of a research question;
You choose the research problem yourself and ask yourself questions. Do not forget that they will need to be briefly justified: explain, based on existing work (with at least one reference to existing research!), why this topic is relevant and requires separate study.


The basis for the question: Does the home environment affect the child's success in mathematics?