STAT TECH IN BUSINESS & ECON AC
18th Edition
ISBN: 9781264731657
Author: Lind
Publisher: MCG
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Chapter 18, Problem 1.8PT
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Chapter 18 Solutions
STAT TECH IN BUSINESS & ECON AC
Ch. 18 - Prob. 1ECh. 18 - Prob. 2ECh. 18 - Prob. 3ECh. 18 - Prob. 4ECh. 18 - Prob. 1SRCh. 18 - Prob. 5ECh. 18 - Prob. 6ECh. 18 - Prob. 7ECh. 18 - Prob. 8ECh. 18 - Prob. 2SR
Ch. 18 - Prob. 9ECh. 18 - Prob. 10ECh. 18 - Prob. 11ECh. 18 - Prob. 12ECh. 18 - Prob. 3SRCh. 18 - Prob. 13ECh. 18 - Prob. 14ECh. 18 - Prob. 15ECh. 18 - Prob. 16ECh. 18 - Prob. 17ECh. 18 - Prob. 18ECh. 18 - Prob. 4SRCh. 18 - Prob. 19ECh. 18 - Prob. 20ECh. 18 - Prob. 21ECh. 18 - Prob. 22ECh. 18 - Prob. 23CECh. 18 - Prob. 24CECh. 18 - Prob. 25CECh. 18 - Prob. 26CECh. 18 - Prob. 27CECh. 18 - Prob. 28CECh. 18 - Prob. 29CECh. 18 - Prob. 30CECh. 18 - Prob. 31CECh. 18 - Prob. 32CECh. 18 - Prob. 33CECh. 18 - Prob. 34CECh. 18 - Prob. 35CECh. 18 - Prob. 1PCh. 18 - Prob. 2PCh. 18 - Prob. 3PCh. 18 - Prob. 1.1PTCh. 18 - Prob. 1.2PTCh. 18 - Prob. 1.3PTCh. 18 - Prob. 1.4PTCh. 18 - Prob. 1.5PTCh. 18 - Prob. 1.6PTCh. 18 - Prob. 1.7PTCh. 18 - Prob. 1.8PTCh. 18 - Prob. 1.9PTCh. 18 - Prob. 1.10PTCh. 18 - Prob. 2.1PTCh. 18 - Prob. 2.2PTCh. 18 - Prob. 2.3PT
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- Match each statement regarding the z-scores of the x and y scores (Zx and Zy) from a scatterplot to the appropriate correlation. Zx scores are both positive and negative ✔ [ Choose ] and Zy scores are mostly close to 0 Most positive Zx scores are paired with positive Zy scores Most positive Zx scores are paired with negative Zy scores A slight majority of negative Zx scores are paired with a slight majority of positive Zy scores moderate negative correlation no correlation strong negative correlation strong positive correlation [Choose ] [Choose ]arrow_forwardIf it has been determined that there exists a very strong linear relationship between two variables, a and y, then O a. It can be assumed that x causes a change in y O b. No correct answer O c. It can be assumed that y causes a change in x O d. A causal relationship between x and y may not exist.arrow_forwardQ11. Simple linear correlation coefficient r can provide the direction, but not the strength of association between two continuous variables. a. TrueB. FalseC. None of the abovearrow_forward
- The numerical value for a correlation_____ can never be less than -1.00 can never be greater than 1.00 and be never be less than -1.00 Can be greater than 1.00 and can be less than -1.00 Can never be greater than 1.00arrow_forwardIn the simple linear regression model, if there is a very strong correlation between the independent and dependent variables, then the correlation coefficient should be a) close to either -1 or +1 b) close to zero c) close to -1 d) close to +1 ( don't hand writing solution)arrow_forwardThe variables X and Y are significantly correlated. Which of the following can you safely conclude about X and Y? a - The variable X causes the variable Y b - A third variable causes both X and Y c - There is a relationship between X and Y d - None of the abovearrow_forward
- If the coefficient of correlation is a negative value, then the coefficient of determination _____. Select one: A. must be positive B. can be either negative or positive C. must also be negative D. must be 0arrow_forwardA large sample of data is collected in order to study the relationship between the two variables X and Y to investigate whether X can be used to predict the value of Y. It is found that r= -75. Which one of the following statements is true? X and Y are perfectly linear correlated and Y decreases as X increases O X and Y are moderately linear correlated and Y increases as X increases X and Y are perfectly linear correlated and Y increases as X increases O X and Y are moderately linear correlated and Y decreases as X increasesarrow_forwardPrincipal components analysis is best suited for O A. none of these B. highly correlated variables C. all variables D. uncorrelated variablesarrow_forward
- In which of the below types of correlation only two variables can be studied? O a. Simple correlation O b. Partial correlation O C. Multiple correlation O d. Linear correlationarrow_forwardExample 15.3 Given the following data. Find whether A and B are independent or associated. n. = 150, (A) = 30, (B) = 60, (ii) (AB) = 256, (aß) = 144, (AB) = 48, (AB) = 12 (aB) = 768arrow_forwardAccording to the concept of ______, two variables are associated when information about one can help us improve our prediction of the other. a. measure of association b. proportional reduction of error c. Pearson’s correlation coefficient d. Cramer’s Varrow_forward
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