MCQs

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Overall MCQs for Reference

What is the primary use of the Chi-Squared test in machine learning?
a. Regression analysis
b. Feature selection for categorical data
c. Dimensionality reduction
d. Ensemble modeling
Answer: bgeeksforgeeks
In a Chi-Squared test, what does a low p-value indicate?
a. Strong relationship between variables
b. Weak relationship between variables
c. Data is normally distributed
d. Data is continuous
Answer: asimplilearn
Which of the following is a requirement for valid application of the Chi-Squared test?
a. Data must be numerical
b. All expected frequencies should be at least 5
c. Data must be continuous
d. Sample size should be below 10
Answer: bpowerdrill
The formula for the Chi-Squared statistic is:
a. ∑(O-E)
b. ∑(O-E)^2/E
c. ∑(O-E)^2/O
d. ∑E/O
Answer: bgeeksforgeeks+1
What is the null hypothesis in a Chi-Squared test of independence?
a. Variables are dependent
b. Variables are independent
c. Sample means are equal
d. Distributions are normal
Answer: bgeeksforgeeks
In a contingency table with 4 rows and 3 columns, degrees of freedom is:
a. 6
b. 7
c. 9
d. 12
Answer: aaskfilo
Why is the Chi-Squared test commonly used in AI for feature selection?
a. To identify linear relationships
b. To find categorical attribute relevance
c. To evaluate regression coefficients
d. To predict time series
Answer: bgeeksforgeeks
Which distribution does the Chi-Squared test statistic follow?
a. Normal
b. t-distribution
c. Chi-Squared
d. Uniform
Answer: cscribd
If the calculated Chi-Squared statistic is greater than the critical value, what decision is made?
a. Accept null hypothesis
b. Reject null hypothesis
c. Cannot decide
d. Accept alternative hypothesis
Answer: baskfilo
For which type of data is the Chi-Squared test not appropriate?
a. Categorical
b. Ordinal
c. Numerical continuous
d. Nominal
Answer: cpowerdrill
What does a Chi-Squared test measure in a machine learning context?
a. Difference between expected and observed frequencies
b. Linear correlation
c. The slope of regression
d. Variance of errors
Answer: asimplilearn+1
In the context of AI, the Chi-Squared test helps in:
a. Regression
b. Feature importance ranking
c. Data normalization
d. Outlier detection
Answer: bgeeksforgeeks
What is the minimum sample size generally recommended for the Chi-Squared test?
a. 2
b. 5
c. 10
d. 20
Answer: dpowerdrill
Which of the following is computed using the Chi-Squared formula?
a. Difference of means
b. Closeness of distributions
c. Square error sum
d. Probability of correlation
Answer: bgeeksforgeeks
The Chi-Squared statistic increases when:
a. Observed and expected frequencies are very close
b. Observed and expected frequencies are very different
c. Sample size decreases
d. Degrees of freedom are reduced
Answer: bscribd+1
What is the typical significance level ( ) used in hypothesis testing with Chi-Squared?
a. 0.01
b. 0.05
c. 0.10
d. 0.50
Answer: bsimplilearn
What happens if expected frequency in any category is less than 5?
a. Chi-Squared test remains valid
b. May lead to incorrect results
c. Results are more accurate
d. p-value increases
Answer: bpowerdrill
What is the sum of all expected frequencies in a Chi-Squared test?
a. Sample size
b. Degrees of freedom
c. Critical value
d. Mean of observed frequencies
Answer: asimplilearn
How is the expected frequency for a cell in a contingency table calculated?
a. Row Total × Column Total/Grand Total
b. Row Total + Column Total
c. Row Total × Column Total
d. Grand Total/Number of cells
Answer: asimplilearn
If the observed and expected frequencies are identical, Chi-Squared value is:
a. Zero
b. One
c. Negative
d. Positive
Answer: aitfeature
Which hypothesis does the Chi-Squared test for feature selection in AI directly test?
a. Regression coefficients
b. Association between feature and target
c. Independence of errors
d. Constant variance
Answer: bgeeksforgeeks
The Chi-Squared test cannot be used when:
a. Data is continuous
b. Categories are mutually exclusive
c. Frequency data is available
d. Data is categorical
Answer: apowerdrill
What does a higher value of the Chi-Squared statistic indicate?
a. Strong evidence against null hypothesis
b. Strong evidence for null hypothesis
c. Fewer categories
d. More independent variables
Answer: ascribd+1
What is the main assumption of the Chi-Squared test in a machine learning context?
a. Normality
b. Independence of observations
c. Homoscedasticity
d. Linearity
Answer: bpowerdrill
When using the Chi-Squared test for independence, the test is invalid if:
a. Observed frequencies are less than 5
b. Categories are not exclusive
c. Observations are not independent
d. All of the above
Answer: dpowerdrill
Which of the following best describes how Chi-Squared test helps in feature selection in AI?
a. Identifies most relevant numerical features
b. Measures association between categorical features and label
c. Ranks features by variance
d. Selects features with highest mean value
Answer: bgeeksforgeeks
In supervised learning, why might you apply a Chi-Squared test?
a. To optimize hyperparameters
b. To select categorical variables strongly associated with target class
c. To standardize input features
d. To prune decision tree branches
Answer: bgeeksforgeeks
The degree of freedom for an r × c contingency table is:
a. (r−1)×(c−1)
b. (r+c−1)
c. (r×c)−1
d. (r+c)
Answer: asimplilearn
In a Chi-Squared test, if the Chi-Squared value is less than the critical value, we:
a. Accept null hypothesis
b. Reject null hypothesis
c. Accept alternative hypothesis
d. Reduce sample size
Answer: aaskfilo
When comparing categorical features in a dataset, which test is most appropriate?
a. Z-test
b. t-test
c. Chi-Squared test
d. F-test
Answer: cgeeksforgeeks
A Chi-Squared value of zero means:
a. No difference between observed and expected
b. Critical value is reached
c. null hypothesis is rejected
d. Model is overfitted
Answer: aitfeature
What does ‘O’ stand for in the Chi-Squared formula ?
a. Observed frequency
b. Order of magnitude
c. Original value
d. Output
Answer: ageeksforgeeks
If calculated Chi-Squared statistic is greater than table value at significance level α, which statement is correct?
a. Accept H0
b. Reject H0
c. Fail to take a decision
d. Increase significance level
Answer: bscribd
The Chi-Squared test can be used to check:
a. Independence of two categorical variables
b. Equality of means
c. Correlation of variables
d. Linear relationship between variables
Answer: asimplilearn+1
What is the alternative hypothesis in the Chi-Squared test for feature selection?
a. No association between feature and label
b. Independence of feature
c. Association between feature and label exists
d. Feature is numerical
Answer: cgeeksforgeeks
When can the results of a Chi-Squared test be misleading?
a. Large sample size
b. Small expected frequencies
c. Using continuous data
d. Both b and c
Answer: dpowerdrill
What is commonly used “threshold” for the p-value to determine significance in a Chi-Squared AI feature selection test?
a. 1
b. 0.1
c. 0.05
d. 0.5
Answer: csimplilearn
What type of hypothesis test is Chi-Squared in feature selection?
a. One-tailed
b. Two-tailed
c. Non-parametric
d. Parametric
Answer: cgeeksforgeeks
Expected frequencies in a contingency table are derived from:
a. Uniform distribution
b. Observed frequencies
c. Marginal totals of columns and rows
d. Standard normal distribution
Answer: csimplilearn
One limitation of the Chi-Squared test in AI applications is:
a. Only works for numeric features
b. Only works on categorical features
c. Cannot test association
d. Only works on small datasets
Answer: bgeeksforgeeks
What happens if the sample size increases dramatically?
a. Chi-Squared loses power
b. Chi-Squared test becomes less significant
c. Small differences might appear statistically significant
d. Observed frequencies decrease
Answer: cpowerdrill
The Chi-Squared value is:
a. Always negative
b. Always positive or zero
c. Always greater than one
d. Ranges between -1 and 1
Answer: bitfeature
For which model selection process is Chi-Squared mainly useful?
a. Linear regression
b. Categorical variable selection
c. Deep learning training
d. SVM hyperparameter tuning
Answer: bgeeksforgeeks
If a Chi-Squared test for independence returns p > 0.05, what conclusion is most supported?
a. Reject the null hypothesis
b. Fail to reject the null hypothesis
c. Prove the alternative hypothesis
d. Significant difference exists
Answer: bsimplilearn
Chi-Squared test is inappropriate for:
a. Testing association between independent numeric variables
b. Testing association between two categorical variables
c. Feature selection in text classification
d. Categorical data analysis
Answer: apowerdrill
In AI, Chi-Squared feature selection is best for:
a. Continuous variables
b. Highly correlated features
c. Nominal and ordinal categorical data
d. Data with high variance
Answer: cgeeksforgeeks
Size of the Chi-Squared statistic is determined by:
a. Theoretical probability distribution
b. Sum of squared difference between observed and expected frequencies
c. Average value of frequencies
d. Ratio of observed to expected
Answer: bgeeksforgeeks
The critical value for a Chi-Squared test is determined by:
a. Mean and variance
b. Degrees of freedom and significance level
c. Sample mean
d. Correlation coefficient
Answer: baskfilo+1
What is the implication if two variables are found dependent by a Chi-Squared test?
a. They are highly correlated
b. There is an association between variables
c. Feature selection must be repeated
d. Test must be repeated
Answer: bsimplilearn+1
Why is data cleansing important before running a Chi-Squared test in AI?
a. To make frequencies equal
b. To ensure no missing and correct categorical data
c. To convert categorical data to continuous
d. To reduce the sample size
Answer: bpowerdrill

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