Use the following regression results to answer the question below. How many observations were involved in this regression? | 8
When a correlation is found between a pair of variables, this always means that there is a direct cause and effect relationship between the variables. | F
A perfect correlation between two variables will always produce a correlation coefficient of +1.0 | F
When constructing a scatter plot, the dependent variable is placed on the vertical axis and the independent variable is placed on the horizontal axis. | T
In a university statistics course a correlation of -0.8 was found between numbers of classes missed and course grade. This means that the fewer classes students missed, the higher the grade. | T
A study was recently done in which the following regression output was generated using Excel. SUMMARY OUTPUT Given this, we know that approximately 57 percent of the variation in the y variable is explained by the x variable. | T
The difference between a scatter plot and a scatter diagram is that the scatter plot has the independent variable on the x-axis while the independent variable is on the Y-axis in a scatter diagram. | F
A research study has stated that the taxes paid by individuals is correlated at a .78 value with the age of the individual. Given this, the scatter plot would show points that would fall on straight line on a slope equal to .78. | False
A bank is interested in determining whether its customers' checking balances are linearly related to their savings balances. A sample of n = 20 customers was selected and the correlation was calculated to be +0.40. If the bank is interested in testing to see whether there is a significant linear relationship between the two variables using a significance level of 0.05, the value of the test statistic is approximately t = 1.8516. | T
A study was recently done in which the following regression output was generated using Excel. SUMMARY OUTPUT Given this output, we would reject the null hypothesis that the population regression slope coefficient is equal to zero at the alpha = 0.05 level. | T
If two variables are spuriously correlated, it means that the correlation coefficient between them is near zero. | F
The correlation coefficient between variables X and Y is positive and close to 1. The relationship between the variables X and Y is _ | a strong linear relationship and as X increases, Y increases
The following regression model has been computed based on a sample of twenty observations: = 34.2 + 19.3x. The first observations in the sample for y and x were 300 and 18, respectively. Given this, the residual value for the first observation is approximately 81.6. | F
An article reported on the topics that teenagers most want to discuss with their parents. The findings, the results of a poll, showed that 33% would like more discussion about the family’s financial situation, 37% would like to talk about school, and 30% would like to talk about religion. These and other percentages were based on a national sampling of 549 teenagers . Estimate the proportion of all teenagers who want more family discussions about school. Use a 99% confidence level. Let z0.005 = 2.58 and z0.01 = 2.33 | (0.317, 0.423)
A study was recently performed by the Internal Revenue Service to determine how much tip income waiters and waitresses should make based on the size of the bill at each table. A random sample of bills and resulting tips were collected and the following regression results were observed: SUMMARY OUTPUT Given this output, the upper limit for the 95 percent confidence interval estimate for the true regression slope coefficient is approximately 0.28. | T
A manufacturing company is interested in predicting the number of defects that will be produced each hour on the assembly line. The managers believe that there is a relationship between the defect rate and the production rate per hour. The managers believe that they can use production rate to predict the number of defects. The following data were collected for 10 randomly selected hours. Defects Production Rate Per Hour 20 400 30 450 10 350 20 375 30 400 25 400 30 450 20 300 10 300 40 300 Given these sample data, the simple linear regression model for predicting the number of defects is approximately = 5.67 + 0.048x. | T
The following regression model has been computed based on a sample of twenty observations: = 34.2 + 19.3x. Given this model, the predicted value for y when x = 40 is 806.2. | T
