ANOVA in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a one-way ANOVA test using the built-in aov function.

R Programming

result <- aov([1] ~ group, data = data_frame)

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

Agroup

Bvalue

Cdata_frame

Danova

Attempts:

3 left

💡 Hint

Common Mistakes

Using the group variable as the dependent variable.

Using the data frame name instead of the variable.

The aov function requires a formula where the dependent variable is on the left side of ~. Here, value is the dependent variable.

2fill in blank

medium

Complete the code to display the summary of the ANOVA test results.

R Programming

summary([1])

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Agroup

Bdata_frame

Cresult

Daov

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the data frame instead of the ANOVA result.

Passing the group variable instead of the model.

The summary function is used to show the ANOVA table from the aov result stored in result.

3fill in blank

hard

Fix the error in the code to correctly perform ANOVA on the variable score grouped by treatment.

R Programming

anova_result <- aov(score [1] treatment, data = df)

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A*

B-

C+

D~

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' or '-' instead of '~' in the formula.

Omitting the formula operator.

The formula in aov requires the tilde ~ to separate the dependent and independent variables.

4fill in blank

hard

Fill both blanks to create a dictionary of means for each group and filter groups with mean greater than 5.

R Programming

group_means <- tapply(df$[1], df$[2], mean)
filtered_means <- group_means[group_means > 5]

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Ascore

Btreatment

Cgroup

Dvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the variable and group names.

Using incorrect variable names.

tapply applies the mean function to score grouped by treatment. Then we filter means greater than 5.

5fill in blank

hard

Fill all three blanks to create a boxplot of response by condition with custom colors and title.

R Programming

boxplot([1] ~ [2], data = experiment_data, col = [3], main = "Response by Condition")

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Aresponse

Bcondition

Cc("red", "blue", "green")

Dc("green", "yellow", "purple")

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping response and condition in the formula.

Using invalid color vectors.

The boxplot formula is response ~ condition. The colors are set with a vector of color names.