ISYE 6414-REGRESSION ANALYSIS
PROJECT REPORT PRACTICE
EXAMINATION 2026 QUESTIONS WITH
ANSWERS GRADED A+
◍ What are the assumptions in residual analysis?.
Answer: 1. Linearity assumption - if there is a nonlinear shape to the data.2.
Constant variance assumptions. - the residuals increase with the X variable3.
Independence assumption - if there are clusters of residuals4. Normality
assumption - using a normal probability plot (if it has a curviture then it is
showing non-normality)
◍ What demographic variables could be used to predict crime rates across
counties?.
Answer: Differences in demographic variables, economic performance, and
police spending per capita.
◍ The estimated versus predicted regression line for a given x*:A) Have the
same varianceB) Have the same expectationC) Have the same variance and
expectationD) None of the above.
Answer: B) Have the same expectation
◍ The mean squared errors (MSE) measures:A) The within-treatment
variability.B) The between-treatment variability.C) The sum of the
within-treatment and between-treatment variability.D) None of the above.
Answer: A) The within-treatment variability.
◍ How many multiple linear regression equations must be estimated?.
Answer: At least three, with at least three explanatory variables.
◍ In simple linear regression models, we lose three degrees of freedom
, because of the estimation of the three model parameters β 0 , β 1 , σ 2.A)
TrueB) False.
Answer: B) False
◍ What does the 'Value of Putt' variable represent?.
Answer: The difference in tournament rankings and monetary prize between
making and missing a putt.
◍ What descriptive statistics are presented in Table 1?.
Answer: Mean, standard deviation, minimum, and maximum for various
variables.
◍ Which one is correct?A) The prediction intervals need to be corrected for
simultaneous inference when multiple predictions are made jointly.B) The
prediction intervals are centered at the predicted value.C) The sampling
distribution of the prediction of a new response is a t-distribution.D) All of
the above.
Answer: D) All of the above
◍ What is the expected length of the final project paper?.
Answer: 10 to 15 pages.
◍ What is the p-value?.
Answer: The p-value is a measure of how reject-able the null hypothesis is.
The smaller the p-value, the more reject-able the null hypothesis is for the
observed data.
◍ (multiple linear regression) What is the process for testing subsets of
coefficients?.
Answer: basically you first measure the sum of squares explained by using
only X1 to predict Y, then you calculate the extra sum of squares explained
by adding X2, then X3, etc. until you get to the last predictor.
◍ What is the primary motivation for using regression?.
Answer: TO use the regression equation to predict future responses.
◍ What should the conclusion section summarize?.
, Answer: The results from the regression models and their implications for
policy.
◍ What is the key question in the example project about golfers?.
Answer: How performance under pressure affects putting success.
◍ What issue was found during the regression analysis regarding standard
errors?.
Answer: Heteroskedasticity was found, requiring correction of standard
errors.
◍ What are dummy variables?.
Answer: In a specific analysis like linear regression where you have
categorical variables, transforming them into dummy variables means
putting 1 for the points that have values and 0 for the rest of the values.
◍ In residual analysis, if the quantile-quantile normal plot and the histogram
show departure from normality, what would be the next step in your
analysis?.
Answer: Consider a transformation of the data in order to normalize it.
◍ The only assumptions for a simple linear regression model are linearity,
constant variance, and normality.A) TrueB) False.
Answer: B) False
◍ What are the three main factors for project evaluation?.
Answer: Econometric/statistical competence, presentation, and reflection.
◍ What is the difference between estimation and prediction?.
Answer: If X is one of the observations for the predicting variable, then we
use estimation. Estimated regression line for the value X is interpreted as the
average estimated mean response for all settings under which the predicting
variable is equal to X*If X is a new observation of the predicting variables,
then we use prediction. Predicted regression line for the value X is
interpreted as the estimated mean response for one setting under which the
predicting variable is equal to X*
PROJECT REPORT PRACTICE
EXAMINATION 2026 QUESTIONS WITH
ANSWERS GRADED A+
◍ What are the assumptions in residual analysis?.
Answer: 1. Linearity assumption - if there is a nonlinear shape to the data.2.
Constant variance assumptions. - the residuals increase with the X variable3.
Independence assumption - if there are clusters of residuals4. Normality
assumption - using a normal probability plot (if it has a curviture then it is
showing non-normality)
◍ What demographic variables could be used to predict crime rates across
counties?.
Answer: Differences in demographic variables, economic performance, and
police spending per capita.
◍ The estimated versus predicted regression line for a given x*:A) Have the
same varianceB) Have the same expectationC) Have the same variance and
expectationD) None of the above.
Answer: B) Have the same expectation
◍ The mean squared errors (MSE) measures:A) The within-treatment
variability.B) The between-treatment variability.C) The sum of the
within-treatment and between-treatment variability.D) None of the above.
Answer: A) The within-treatment variability.
◍ How many multiple linear regression equations must be estimated?.
Answer: At least three, with at least three explanatory variables.
◍ In simple linear regression models, we lose three degrees of freedom
, because of the estimation of the three model parameters β 0 , β 1 , σ 2.A)
TrueB) False.
Answer: B) False
◍ What does the 'Value of Putt' variable represent?.
Answer: The difference in tournament rankings and monetary prize between
making and missing a putt.
◍ What descriptive statistics are presented in Table 1?.
Answer: Mean, standard deviation, minimum, and maximum for various
variables.
◍ Which one is correct?A) The prediction intervals need to be corrected for
simultaneous inference when multiple predictions are made jointly.B) The
prediction intervals are centered at the predicted value.C) The sampling
distribution of the prediction of a new response is a t-distribution.D) All of
the above.
Answer: D) All of the above
◍ What is the expected length of the final project paper?.
Answer: 10 to 15 pages.
◍ What is the p-value?.
Answer: The p-value is a measure of how reject-able the null hypothesis is.
The smaller the p-value, the more reject-able the null hypothesis is for the
observed data.
◍ (multiple linear regression) What is the process for testing subsets of
coefficients?.
Answer: basically you first measure the sum of squares explained by using
only X1 to predict Y, then you calculate the extra sum of squares explained
by adding X2, then X3, etc. until you get to the last predictor.
◍ What is the primary motivation for using regression?.
Answer: TO use the regression equation to predict future responses.
◍ What should the conclusion section summarize?.
, Answer: The results from the regression models and their implications for
policy.
◍ What is the key question in the example project about golfers?.
Answer: How performance under pressure affects putting success.
◍ What issue was found during the regression analysis regarding standard
errors?.
Answer: Heteroskedasticity was found, requiring correction of standard
errors.
◍ What are dummy variables?.
Answer: In a specific analysis like linear regression where you have
categorical variables, transforming them into dummy variables means
putting 1 for the points that have values and 0 for the rest of the values.
◍ In residual analysis, if the quantile-quantile normal plot and the histogram
show departure from normality, what would be the next step in your
analysis?.
Answer: Consider a transformation of the data in order to normalize it.
◍ The only assumptions for a simple linear regression model are linearity,
constant variance, and normality.A) TrueB) False.
Answer: B) False
◍ What are the three main factors for project evaluation?.
Answer: Econometric/statistical competence, presentation, and reflection.
◍ What is the difference between estimation and prediction?.
Answer: If X is one of the observations for the predicting variable, then we
use estimation. Estimated regression line for the value X is interpreted as the
average estimated mean response for all settings under which the predicting
variable is equal to X*If X is a new observation of the predicting variables,
then we use prediction. Predicted regression line for the value X is
interpreted as the estimated mean response for one setting under which the
predicting variable is equal to X*
