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Statistical Modeling Quiz :Statistics Foundations (Meta Marketing Analytics Professional Certificate) Answers 2025

Question 1

Consider the assumptions in simple linear regression. What is the assumption of normality?

  • ❌ The independent variables do not affect one another.

  • The data creates a normal distribution.

  • ❌ The minimum sample is 20.

  • ❌ All independent variables have similar variance.


Question 2

Which one of the following is a modeling technique in clustering analysis?

  • ❌ I. Simple linear regression

  • II. K-means

  • ❌ III. Logistic regression

  • ❌ All of them


Question 3

In time series analysis, what does the assumption of dependence mean?

  • That the dependent variable depends on the independent variable.

  • ❌ That all the observations come from the same place.

  • ❌ That time must be one of the independent variables.

  • ❌ That the dependent variable does not change over time.


Question 4

In time series analysis, one of the independent variables must be time.

  • ❌ False

  • True


Question 5

What is the difference between a classification model and a regression model?

  • ❌ A classification model is used with numerical data, while a regression model works with qualitative variables.

  • ❌ A classification model predicts a quantitative variable, while a regression model predicts a qualitative variable.

  • A classification model predicts a qualitative variable, while a regression model predicts a quantitative variable.

  • ❌ A classification model is used with qualitative data, while a regression model works with categorical data.


Question 6

What is the assumption equal prior probability for K-means clustering?

  • That each cluster has the same probability of happening.

  • ❌ That each data value has the same probability of occurring.

  • ❌ That one of the clusters is more likely to occur than the others.

  • ❌ That each cluster has the same number of data points.


Question 7

In time series there are three assumptions: minimum sample size, dependence, and:

  • ❌ independence.

  • ❌ normality.

  • stationarity.

  • ❌ homogeneity.


Question 8

In time series analysis, what is the assumed minimum sample size if time is measured in quarters?

  • 40 quarters of information.

  • ❌ 50 quarters of information.

  • ❌ 100 quarters of information.

  • ❌ 4 quarters of information.


Question 9

Which of the following is an assumption in simple linear regression?

I. Independence
II. Sphericity
III. Dependence

  • I.

  • ❌ All of them are.

  • ❌ III.

  • ❌ II.


Question 10

Which of the following is a type of quantitative variable?

  • ❌ Dependent.

  • ❌ Categorical.

  • ❌ Independent.

  • Continuous.


🧾 Summary Table

Q# ✅ Correct Answer Key Concept
1 The data creates a normal distribution Normality assumption in regression
2 K-means Clustering method
3 Dependent variable depends on independent variable Dependence in time series
4 True Time must be a variable
5 Classification → qualitative, Regression → quantitative Model type difference
6 Each cluster has same probability Equal prior probability
7 Stationarity Constant mean/variance assumption
8 40 quarters Minimum sample size for time series
9 Independence Regression assumption
10 Continuous Quantitative variable type