For a sample of 40 large U.S. cities, the correlation between the mean number of square feet per office worker and the mean monthly rental rate in the central business district is -0.363.  At the .05 significance level, can we conclude that there is a negative association between the two variables.

Which of the following is an example of a negative correlation?Question 12Answera.The rate of heart attacks is directly proportional to yearly income.b.Shoe size increases as height increases.c.Body weight increases as children get older.d.The likelihood of owning a baseball card collection decreases with age.

State the correlation between number of hours spent in the mall and amount of money spent. a. Positive Correlation b. Negative Correlation c. No Correlation

Which of the following data sets would most likely have a negative association and a correlation coefficient between 0 and -1? a.) Swimsuit sales throughout the year Sunscreen sales throughout the year b.) Steepness of the Appalachian Trail John's speed while hiking up the Appalachian Trail c.) Number of miles driven by Paul Number of gallons of gas used by Paul's car d.) Average Summer temperature in the United States Summer air-conditioning costs for homes in the United States

Average Family Income Rentals 62 705 41 525 27 309 45 498 50 623 47 425 44 314 28 203 30 465 41 540 47 605 62 690 Create an Excel spreadsheet and enter the data using income as the independent variable (predictor) and number of daily rentals as the dependent variable (criterion). (a) Use Excel’s 1⁄4 correl function to find the correlation between these two variables, and round off the result to two decimal places. (b) Create an XY scatterplot of these two sets of data such that: • Top title: RELATIONSHIP BETWEEN INCOME AND RENTALS/DAY • x-axis title: AVERAGE FAMILY INCOME ($000) • y-axis title: RENTALS (per day) • re-size the chart so that it is 8 columns wide and 25 rows long • move the chart below the table (c) Create the least-squares regression line for these data on the scatterplot. (d) Use Excel to run the regression statistics to find the equation for the least squares regression line for these data and display the results below the chart on your spreadsheet. Use number format (2 decimal places) for the correlation and for the coefficients Now, answer these questions using your Excel: (1) What is the y-intercept? (2) What is the slope of the line? (3) What is the regression equation for these data (use two decimal places for the y-intercept and the slope)? (4) Use the regression equation to predict the average number of daily rentals you would expect for a retail area that had an average family income of $50,000.

There is a correlation of r = −.74 between the cost of bananas and new passenger car sales in the United States (Vigen, n.d.). Which of the following is an appropriate conclusion? 1 pointAn increase in the cost of bananas causes a decrease in new passenger car sales.There is a statistically significant relationship between the cost of bananas and new passenger car sales.As the cost of bananas decreases, new passenger car sales decrease.As the cost of bananas increases, new passenger car sales decrease.