QRM 3

In logistic regression a condition is for the X’s to be:

• Normally distributed

• Evenly distributed

In this course, we can use logistic regression analysis when we have any kind of nominal scaled Y-variable and some continuous scaled X-variables:

• True

• False

• Trend model

• Autoregressive model (AR1)

• Moving averages

The Durbin Watson observation value ranges from:

• 0-4

• 0-10

• 4-10

“a positive error is followed by another positive one, and a negative error is followed by another negative one” describes:

• Positive autocorrelation

• No autocorrelation

• Negative autocorrelation

Are time series good at forecasting a change “in direction”?

• Yes

• No

A Durbin Watson value close to 4 indicates:

• Positive autocorrelation

• No autocorrelation

• Negative autocorrelation

The rule of thumb for “P(success) is not too extreme” is the ratio:

• 60/40

•  80/20

• 50/50

In logistic regression, which measure relates to how good the model is at predicting the right outcome

• Odds ratio

• Parameter Estimates

• Hit Ratio