ANOVA in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the ANOVA function from scipy.stats.

Data Analysis Python

from scipy.stats import [1]

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

Apearsonr

Bchi2_contingency

Cf_oneway

Dttest_ind

Attempts:

3 left

💡 Hint

Common Mistakes

Importing ttest_ind instead of f_oneway

Using pearsonr which is for correlation

Using chi2_contingency which is for categorical data

The f_oneway function from scipy.stats is used to perform one-way ANOVA.

2fill in blank

medium

Complete the code to perform one-way ANOVA on three groups: group1, group2, and group3.

Data Analysis Python

stat, p = f_oneway([1], group2, group3)

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

Adata

Bgroup1

Cgroup4

Dsamples

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable that does not exist like group4

Using the whole dataset instead of individual groups

The first argument to f_oneway should be the first group of data, here group1.

3fill in blank

hard

Fix the error in the code to correctly perform ANOVA on three groups stored in a list called data_groups.

Data Analysis Python

stat, p = f_oneway(*[1])

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

Adata_groups

Bdata_groups[0]

Cdata_groups()

Ddata_groups[:]

Attempts:

3 left

💡 Hint

Common Mistakes

Passing only the first group instead of all groups

Calling the list as a function which causes an error

The asterisk * unpacks the list data_groups so each group is passed as a separate argument.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each group name to its mean value.

Data Analysis Python

group_means = {name: [1] for name, data in [2].items()}

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

Adata.mean()

Bdata.sum()

Cgroups

Dgroup_data

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum instead of mean

Using the wrong dictionary name

The comprehension calculates the mean of each group's data. The dictionary groups holds the group names and data.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that includes only groups with mean greater than 50.

Data Analysis Python

filtered_means = {name: mean for name, mean in [1].items() if mean [2] [3]

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

Agroup_means

B>

C50

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using less than operator instead of greater than

Using the wrong dictionary variable

This comprehension filters the group_means dictionary to keep only groups with mean values greater than 50.

Practice

1.

What is the main purpose of ANOVA in data analysis?

easy

A. To predict future values using regression

B. To check if three or more groups have different average values

C. To find the median of a dataset

D. To calculate the correlation between two variables

Solution

1. Step 1: Understand the goal of ANOVA

   ANOVA is used to compare the means of three or more groups to see if at least one group mean is different.

2. Step 2: Differentiate from other tests

   Correlation measures relationships, median finds middle value, regression predicts values. These are not ANOVA's purpose.

3. Final Answer:

   To check if three or more groups have different average values -> Option B

4. Quick Check:

   ANOVA tests group means difference = To check if three or more groups have different average values [OK]

Hint: ANOVA compares means of 3+ groups, not pairs [OK]

Common Mistakes:

• Confusing ANOVA with correlation
• Thinking ANOVA predicts values
• Using ANOVA for two groups only

2.

Which of the following is the correct way to import the ANOVA function f_oneway from scipy.stats in Python?

easy

A. from scipy.stats import f_oneway

B. import scipy.stats.f_oneway

C. from scipy import f_oneway

D. import f_oneway from scipy.stats

Solution

1. Step 1: Recall Python import syntax

   To import a specific function from a module, use 'from module import function'.

2. Step 2: Match with given options

   from scipy.stats import f_oneway matches this syntax correctly for f_oneway from scipy.stats.

3. Final Answer:

   from scipy.stats import f_oneway -> Option A

4. Quick Check:

   Correct import syntax = from scipy.stats import f_oneway [OK]

Hint: Use 'from module import function' to import specific functions [OK]

Common Mistakes:

• Using 'import module.function' which is invalid
• Swapping import order
• Trying to import function directly without module

3.

Consider the following Python code using scipy.stats.f_oneway:

from scipy.stats import f_oneway

group1 = [5, 7, 8, 6]
group2 = [6, 9, 7, 10]
group3 = [8, 12, 11, 9]

f_stat, p_val = f_oneway(group1, group2, group3)
print(round(f_stat, 2), round(p_val, 3))

What is the output?

medium

A. 7.89 0.001

B. 3.67 0.065

C. 4.44 0.054

D. 1.23 0.345

Solution

1. Step 1: Run the ANOVA test on the groups

   Using f_oneway on the three groups calculates the F-statistic and p-value for differences in means.

2. Step 2: Calculate and round results

   Running the code gives F = 4.44 and p = 0.054 after rounding.

3. Final Answer:

   4.44 0.054 -> Option C

4. Quick Check:

   F-statistic and p-value match 4.44 0.054 [OK]

Hint: Run f_oneway and round results to check output fast [OK]

Common Mistakes:

• Mixing up F-statistic and p-value
• Rounding incorrectly
• Using wrong group data

4.

Identify the error in this ANOVA code snippet:

from scipy.stats import f_oneway

group1 = [4, 5, 6]
group2 = [7, 8, 9]
f_stat, p_val = f_oneway(group1, group2)
print(f_stat, p_val)

Why might this code be problematic?

medium

A. The groups must be numpy arrays, not lists

B. The print statement syntax is incorrect

C. The function f_oneway is not imported correctly

D. ANOVA requires at least three groups, but only two are given

Solution

1. Step 1: Recall ANOVA group requirements

   ANOVA is designed to compare means of three or more groups, not just two.

2. Step 2: Check code groups

   Only two groups are provided, so ANOVA is not appropriate here; a t-test would be better.

3. Final Answer:

   ANOVA requires at least three groups, but only two are given -> Option D

4. Quick Check:

   ANOVA needs 3+ groups = ANOVA requires at least three groups, but only two are given [OK]

Hint: ANOVA needs 3+ groups; 2 groups means use t-test [OK]

Common Mistakes:

• Thinking lists can't be used
• Assuming import error without checking
• Misreading print syntax

5.

You have three groups of exam scores:

groupA = [70, 75, 80, 85]
groupB = [65, 70, 75, 80]
groupC = [90, 92, 88, 94]

You want to know if the average scores differ significantly. After running ANOVA, you get p_val = 0.002. What should you conclude?

hard

A. There is strong evidence that at least one group mean is different

B. All group means are equal because p-value is low

C. The test is inconclusive because p-value is less than 0.05

D. You should run ANOVA again with more groups

Solution

1. Step 1: Interpret the p-value from ANOVA

   A p-value of 0.002 is less than the common threshold 0.05, indicating significant difference.

2. Step 2: Understand what significance means

   Significant p-value means at least one group mean differs from others, rejecting the equal means hypothesis.

3. Final Answer:

   There is strong evidence that at least one group mean is different -> Option A

4. Quick Check:

   p-value < 0.05 means reject equal means = There is strong evidence that at least one group mean is different [OK]

Hint: p-value < 0.05 means groups differ significantly [OK]

Common Mistakes:

• Thinking low p-value means equal means
• Confusing significance with inconclusiveness
• Ignoring p-value threshold