Business Analysis Statistics Test #2

Question 1

A firm has eight regional branch offices.
Customers within each region are coded using the variable name VALUE and are categorized as either "High Value" or "Medium Value." The response variable used in the past year is the total number of purchases made by each client.
Assume REGION and VALUE have a substantial interaction.
What do you draw from this?

Accepted Answer

The disparity between medium and high value clients' average purchases varies by area.

Answer

There are more high value clients in regions with higher average buy levels.

Answer

There are more medium value clients in areas with higher average buy levels.

Answer

Some regions have more high value consumers than others.

Question 2

An existing multiple linear regression model is modified by removing a non-contributing predictor variable (Pr > |t| =0.658). What will happen as a result?

Accepted Answer

A decrease in R-Square

Answer

No change in R-Square

Answer

A decrease in Mean Square Error

Answer

An increase in R-Square

Question 3

The link between a binary response and an ordinal predictor variable, wrist size, is examined in the LOGISTIC method output that follows. The analyst decides on Large (L) as the reference level using reference cell coding. What is a person with a large wrist size's estimated logit? If one is required, simply click the calculator icon to bring one up.

Accepted Answer

-1.0415

Answer

0.5663

Answer

0.0819

Answer

-3.7727

Question 4

In the LOGISTIC process, which of the following best defines a concordant pair of observations?

Accepted Answer

A prediction for an observation that includes the event is higher than for an observation that does not.

Answer

In comparison to an observation without the event, an observation with the event has a lower anticipated probability.

Answer

There is an equal chance that one observation will be associated with the occurrence as another.

Answer

The anticipated probability for an observation with and without the occurrence is the same.

Question 5

You may check for non-linearity in binary logistic regression by visualizing:

Accepted Answer

An empirical logit trend plot against a predictor variable

Answer

Odds ratio values plotted against a predictor variable in a box.

Answer

A plot of projected probability values against a predictor variable using logistic regression.

Answer

Binary response scatterplot vs predictor variable

Question 6

What is the LOGISTIC procedure's default approach to handling observations with incomplete data?

Accepted Answer

Only instances with completely populated variables are employed.

Answer

In order to accommodate for the missing values, parameters are estimated.

Answer

All the data is used to estimate the parameters.

Answer

Missing values are imputed.

Question 7

By examining the correlation between which function of the input variables, Spearman statistics in the CORR technique are helpful for identifying unnecessary variables.

Accepted Answer

Rank-ordered values of the variables

Answer

Concordant and discordant pairs of ranked observations

Answer

Weighted sum of chi-square statistics for 2x2 tables

Answer

Logit link (log(p/1-p))

Question 8

A logistic regression model's input variable, Region (A, B, or C), is investigated by an analyst. The analyst finds that when Region = A, the likelihood of purchasing a specific item is 1. What issue does this highlight?

Accepted Answer

Quasi-complete separation

Answer

Influential observations

Answer

Collinearity

Answer

Problems that arise due to missing values

Question 9

What disadvantage exists in cleaning up the data (imputation, transformations, etc.) on raw data before partitioning it for accurate assessment as opposed to cleaning up the data after partitioning it?

Accepted Answer

It is impossible to compare the efficacy of various washing techniques.

Answer

The advantages of the purification techniques are not applied to the training (and test) data sets.

Answer

It violates assumptions of the model.

Answer

It requires extra computational effort and time.

Question 10

To execute an unbiased evaluation during the model building process, an analyst has access to a large enough volume of data to do a 3-way partitioning of the data into training, validation, and test sets. What goal does the test data set serve?

Accepted Answer

To offer a fair assessment metric for the finished model.

Answer

To reduce total sample size to make computations more efficient.

Answer

To build the predictive models.

Answer

To compare models and select and fine-tune the final model.