Regression and Seasonal Analysis Quiz

A least squares regression line is fitted to data in a scatterplot. Which of the following is the correct residual plot?

• 
• B. Plot B

• C. Plot C

• D. Plot D

• E. Plot E

A student uses the following data to construct a scatterplot: x = 1, 2, 3, 4, 5, 6, 7, 8, 9 and y = 12, 25, 33, 58, 98, 168, 345, 397, 896. After applying a log transformation to the y-axis, which equation is closest to the least squares regression line?

• A. log y = -217 + 88.0x

• B. log y = -3.8 + 4.4x

• C. log y = 3.1 + 0.008x

• D. log y = 0.88 + 0.23x

• E. log y = 1.58 + 0.002x

The seasonal index for October is missing from the table. What is the value of the missing seasonal index for October?

• A. 0.93

• B. 0.95

• C. 0.96

• D. 0.98

• E. 1.03

The deseasonalised number of unemployed in September is 350. What is the closest estimate of the actual number of unemployed in September?

• A. 310

• B. 344

• C. 351

• D. 371

• E. 640

What is the main advantage of using three-median smoothing over three-mean smoothing in time series analysis?

• It is less affected by outliers.

• It is easier to calculate.

• It provides a more detailed trend.

• It requires less data.

According to the smoothed time series, what is the range of the smoothed values for the telephone call costs?

• $200 to $210

• $180 to $220

• $190 to $230

• $210 to $220

What is the response variable in the given data about car depreciation?

• Age of the car

• Brand of the car

• Value of the car

• Model of the car

What transformation is suggested by Scatterplot 1 to linearize the data?

• Exponential transformation

• Logarithmic transformation

• Polynomial transformation

• Square root transformation

In Table 2, what is the log(age) value for a car that is 9 years old?

• 0.85

• 0.90

• 0.95

• 1.00

What type of relationship exists between value and log(age) according to Scatterplot 2?

• Strong positive linear relationship

• Weak positive linear relationship

• Strong negative linear relationship

• Weak negative linear relationship