Chi-squared test in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a chi-squared test on the table 'data_table'.

R Programming

result <- chisq.test([1])

Drag options to blanks, or click blank then click option'

Amatrix()

Bdata.frame

Cdata_table

Dtable()

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a function call like matrix() instead of the table variable.

Using data.frame which is not a contingency table.

The function chisq.test() requires a contingency table as input. Here, data_table is the correct variable representing the table.

2fill in blank

medium

Complete the code to extract the p-value from the chi-squared test result stored in 'result'.

R Programming

p_value <- result$[1]

Drag options to blanks, or click blank then click option'

Astatistic

Bobserved

Cparameter

Dp.value

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'statistic' which gives the test statistic, not the p-value.

Using 'parameter' or 'observed' which are different parts of the result.

The p-value of the chi-squared test is stored in the p.value element of the result object.

3fill in blank

hard

Fix the error in the code to correctly create a contingency table from vectors 'group' and 'outcome'.

R Programming

table_data <- [1](group, outcome)

Drag options to blanks, or click blank then click option'

Atable

Bmatrix

Ccbind

Ddata.frame

Attempts:

3 left

💡 Hint

Common Mistakes

Using cbind which just binds columns without counting.

Using data.frame or matrix which do not create frequency tables.

The table() function creates a contingency table from categorical vectors.

4fill in blank

hard

Fill both blanks to perform a chi-squared test with continuity correction disabled on 'table_data'.

R Programming

result <- chisq.test([1], [2]FALSE)

Drag options to blanks, or click blank then click option'

Atable_data

Bcorrect =

Ccorrect=

Ddata_table

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'correct = ' with spaces around the equals sign.

Passing wrong variable names like 'data_table'.

The first argument is the contingency table variable table_data. The parameter to disable continuity correction is correct=FALSE with no space around the equals sign.

5fill in blank

hard

Fill all three blanks to create a table from 'gender' and 'smoking' vectors, perform a chi-squared test, and extract the test statistic.

R Programming

tab <- [1](gender, smoking)
result <- chisq.test([2])
st <- result$[3]

Drag options to blanks, or click blank then click option'

Atable

Btab

Cstatistic

Ddata.frame

Attempts:

3 left

💡 Hint

Common Mistakes

Using data.frame instead of table.

Passing wrong variable names or extracting wrong elements.

First, create the contingency table with table(). Then pass that table variable tab to chisq.test(). Finally, extract the test statistic with statistic.

Practice

1. What does the Chi-squared test in R primarily check for?

easy

A. Whether two categorical variables are related

B. Whether two numerical variables have the same mean

C. Whether a variable follows a normal distribution

D. Whether the data contains missing values

Solution

1. Step 1: Understand the purpose of the Chi-squared test

   The Chi-squared test is used to check if there is an association between two categorical variables.

2. Step 2: Compare with other options

   Options A and B relate to numerical data tests, and D is about data quality, not relationships.

3. Final Answer:

   Whether two categorical variables are related -> Option A

4. Quick Check:

   Chi-squared test checks categorical variable relationship = C [OK]

Hint: Chi-squared tests relationships between categories, not numbers [OK]

Common Mistakes:

• Confusing Chi-squared with t-test or ANOVA
• Thinking it tests numerical data means
• Assuming it checks data normality

2. Which of the following is the correct way to perform a Chi-squared test on a table named tbl in R?

easy

A. chisq(tbl)

B. chisq.test(tbl)

C. chi.test(tbl)

D. test.chisq(tbl)

Solution

1. Step 1: Recall the correct function name in R

   The function to perform a Chi-squared test in R is chisq.test().

2. Step 2: Check the syntax

   The correct syntax is calling chisq.test() with the table as the argument.

3. Final Answer:

   chisq.test(tbl) -> Option B

4. Quick Check:

   Correct function is chisq.test() = B [OK]

Hint: Use chisq.test() function for Chi-squared test in R [OK]

Common Mistakes:

• Using incorrect function names like chisq() or chi.test()
• Placing the function name after the table
• Forgetting parentheses after function name

3. What will be the output of the following R code?

tbl <- matrix(c(10, 20, 30, 40), nrow=2)
result <- chisq.test(tbl)
round(result$p.value, 3)

medium

A. 0.504

B. 0.025

C. 0.000

D. Error: object 'result' not found

Solution

1. Step 1: Understand the input table

   The matrix has counts: 10, 20 in first row and 30, 40 in second row.

2. Step 2: Perform Chi-squared test and check p-value

   Running chisq.test on this table gives a p-value around 0.504, meaning no strong association.

3. Final Answer:

   0.504 -> Option A

4. Quick Check:

   Chi-squared p-value rounded = 0.504 [OK]

Hint: Check p-value from chisq.test() to judge significance [OK]

Common Mistakes:

• Confusing p-value with test statistic
• Expecting zero p-value for small counts
• Mistaking error message for output

4. Identify the error in this R code snippet for Chi-squared test:

data <- matrix(c(5, 15, 20, 10), ncol=2)
chisq.test(data)

medium

A. Matrix should have rows and columns swapped

B. chisq.test() requires a data frame, not a matrix

C. No error, code runs correctly

D. Matrix must be named 'tbl' to work

Solution

1. Step 1: Check matrix creation

   The matrix is created with 4 values and 2 columns, which is valid.

2. Step 2: Check chisq.test() input type

   chisq.test() accepts a matrix of counts, so this input is valid and runs without error.

3. Final Answer:

   No error, code runs correctly -> Option C

4. Quick Check:

   chisq.test() accepts matrix input = A [OK]

Hint: chisq.test() works with matrices or tables of counts [OK]

Common Mistakes:

• Thinking chisq.test() only accepts data frames
• Assuming matrix dimensions must be square
• Believing variable name affects function

5. You have survey data of 3 groups choosing among 3 products. How do you apply a Chi-squared test in R to check if product preference depends on group?

group <- c('A', 'A', 'B', 'B', 'C', 'C')
product <- c('X', 'Y', 'X', 'Z', 'Y', 'Z')
# What next?

hard

A. Convert group and product to numeric and run chisq.test()

B. Run chisq.test(group, product) directly without table

C. Use t.test() on group and product vectors

D. Create a table with table(group, product) then run chisq.test() on it

Solution

1. Step 1: Create a contingency table

   Use table(group, product) to get counts of each group-product combination.

2. Step 2: Apply Chi-squared test on the table

   Run chisq.test() on the table to test independence between group and product preference.

3. Final Answer:

   Create a table with table(group, product) then run chisq.test() on it -> Option D

4. Quick Check:

   Table then chisq.test() = A [OK]

Hint: Always make a table before chisq.test() for categorical data [OK]

Common Mistakes:

• Trying to run chisq.test() on raw vectors
• Using t.test() instead of chisq.test() for categories
• Converting categories to numbers incorrectly