Which of the following situations treats "deal proneness" as a dependent variable in a relationship? A. Deal proneness is predicted by a person's household income. 8 Deal proneness results in greater price sensitivity. C. Deal proneness predicts the time spent by a person shopping. D Deal proneness leads to greater brand loyalty. The following crosstabulation shows data from a sample of 70 people, broken down by their age (over 45, or 45 and under) and their internet provider (Telstra, or Not Telstra). Telstra Not Telstra TOTAL 45 and under 15 25 40 Over 45 23 7 30 TOTAL 38 32 70 The most appropriate hypothesis test to perform for such data would be: A. Difference between two population means. B. Chi-square test. C. Dependent samples test. D. One sample test. E. Correlation test. A correlation coefficient of -0.1 for two variables based on 200 data points most likely indicates: A. a very weak linear relationship exists between the two variables. 8. a very strong linear relationship exists and, on average, the value of one variable decreases as the value of the other variable increases. C. a nonnlinear relationship must exist. D. an error in calculation has occurred because correlation coefficients cannot be negative. Consider the following simple linear regression model between the dependent variable. SALES (reecting monthly sales, in thousands of dollars) and independent variable, ADVERTISING (representing the monthly advertising expenditure, in thousands of dollars): Expected (SALES) = 4.2 - 2.6 ADVERTISING. The value 2.6 in the above regression model represents: A. the value of SALES, on average. when ADVERTISING is zero. 8. the change in SALES following a unit decrease in ADVERTISING. C. a ratio of SALES over ADVERTISING as a percentage. D. the proportion of the variation in SALES explained by using ADVERTISING in the regression equation. E. a ratio of ADVERTISING over SALES as a percentage