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A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Related questions

Question

You can actually improve model fit by removing (a) predictor(s) in multiple regression.

True

False

Question 2

...................? are observations that fall far from the "cloud" of points

Question 3

What is the best way to describe the point in the yellow box?

a. An outlier fall along from the cloud that appears to influence the direction of the line

b. An outlier close to the least squares line, suggesting that it was likely not very influential

c. An outlier far from the other points that only slightly influences the line, if at all

d. None of these

Question 4

The proper estimate of variance explained in multiple regression is

a. >50% significant predictors

b. Adjusted R²

c. R²

d. All of these

Question 5

Adjusted R² is actually a biased estimate, so we turn to R²

True

False

Question 6

In multiple regression, you can have nominal and continuous predictors

True

False

Question 7

In this regression, which predictor(s) is/are significant?

a. Both

b. 'pubs'

c. Neither

d. 'time'

Question 8

You run a regression for x predicting y and find the p-value to be .04. Which of the following can you say most comfortably?

a. Given the assumptions have been met, y significantly predicts x, but we can't be sure if it is important

b. None of these

c. Only 4% of the time would you expect to find a test statistic as extreme or more, assuming the null hypothesis is true

d. The finding indicates x strongly predicts y

Question 9

Which of the following describes the amount of variation in the response that is explained by the least squares line?

a. S

b. Line of best fit

c. Variability

d. R²

Question 10

Which of the following is true?

a. The t-value was obtained by dividing the estimate by standard error

b. The 'unemp' coefficient is significant

c. A t-value of -1.23 is significant

d. None of these

Question 11

Based on this table, which of the following statements is true?

a. adverts' estimate of .08 shows it is not significant

b. adverts' t-value of -1.53 shows it is a significant predictor

c. adverts' t-value and associated p-value indicate it is a significant predictor

d. None of these

Question 12

The line of best fit in linear regression will be the one that has the maximizes the sum of the squared residuals

True

False

Question 13

Which of the following are assumptions when fitting a least squares line in linear regression? (Select all that apply)

a. Linearity: The data should show a linear trend

b. Nearly normal residuals: generally the residuals must be nearly normal

c. Constant variability: Variability of points around the least squares line must remain roughly constant

d. Symmetry: Lines of best fit should fit symmetrically along the median value

Question 14

When fitting a line to data, the points will (almost) never perfectly fall on the line. The difference between the line of best fit and a point is called a(n)

a. error

b. residual

c. regressor

d. correlation

Question 15 (2 points)

Just by looking at this scatterplot, you'd say the relationship is generally which of the following?

a. No relationship

b. Parabolic

c. Negative

d. Positive

Question 16

Logistic and multiple regression have the same type of outcome variables

True

False

Question 17

What transformation does this represent?

log (p)

(1-p)

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