Cisb 241 Test 2 Chapter 14

If the population correlation between two variables is determined to be -0.70, which of the following is known to be true? Question options: A) There is a fairly strong negative linear relationship between the two variables. B) An increase in one of the variables will cause the other variable to decline by 70 percent. C) There is a positive linear relationship between the two variables. D) The scatter diagram for the two variables will be upward sloping from left to right.

A) There is a fairly strong negative linear relationship between the two variables.

A regression analysis between sales (Y) and advertising (X) (both in dollars) resulted in the following equation: y = 100+200x The above equation implies that an Question options: A) increase of $10 in advertising is correlated with an increase of $100 in sales. B) increase of $10 in advertising is correlated with an increase of $2,000 in sales. C) increase of $10 in advertising is correlated with an increase of $2100 in sales. D) increase of $10 in advertising is correlated with an increase of $20 in sales.

B) increase of $10 in advertising is correlated with an increase of $2,000 in sales.

The following is Excel Data Analysis output for Regression. The data is comparing the customer satisfaction rating (y) based on the drive thru service time in minutes (x): SUMMARY OUTPUT Regression Statistics Multiple R0.8851 R Square0.7835 Adjusted R Square0.7474 Standard Error5.4006 Observations8 ANOVA dfSSMSFSignificant FRegression1633.242633.24221.7110.0034Residual617529.167 Total7808.242 CoefficientsStandard Errort StatP-valueIntercept9.611182.020239042-0.330860.749248Time (Minutes)-0.515510.58279-4.659523.47E-03 Which of the following is true? Question options: A) The correlation coefficient (r) is 0.8851. B) The correlation coefficient (r) is -0.7835. C) The correlation coefficient (r) is -0.8851. D) The correlation coefficient (r) is 0.7835.

C) The correlation coefficient (r) is -0.8851.

A regression test was conducted to help in predicting the price of milk in Colorado (y) based on the gasoline prices in Florida (x). The results showed that there was a strong correlation (r=.85). In looking at the analysis a statistician said the results indicated a spurious correlation. What did the statistician mean by a spurious correlation? Question options: A) The correlation is valid and you can use the cost of gas in Florida to predict the cost of milk in Colorado. B) The test contained mathematical errors. C) The correlation is invalid because it is between two seemingly unrelated variables. D) None of the above.

C) The correlation is invalid because it is between two seemingly unrelated variables.

A study was done to see if the cost of the meal (x) could be used to predict the amount tipped (y). A random sample of bills and resulting tips were collected. The smallest bill was $9 and the largest bill was $89 in the sample. The following regression results were observed: SUMMARY OUTPUT Regression Statistics Multiple R0.9339 R Square0.8722 Adjusted R Square0.8658 Standard Error1.5578 Observations22 ANOVA dfSSMSFSignificant FRegression1331.10987331.10987136.4362.1E-10Residual2048.5368562.4268424 Total21379.646727 CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Intercept-1.23630.7136498-1.73230.09860.2520.254Food Total ($)0.19210.0164453911.68062.1E-100.158 0.226 Given this output, which of the following is true? Question options: A) The point estimate for the slope is 0.192. B) We are 95% confident that the true slope is between .158 and .226. C) y = -1.2362 + .1921 * x for values of x between $9 and $89. D) All of the options are true.

D) All of the options are true.

Let's say we conduct a hypothesis test on the regression slope coefficient (r): Ho p=0 Ha p≠0 We find that the t-value and p-value are not in the tail and we do not reject Ho. This means: Question options: A) there is not enough evidence to show there is a linear correlation. With the given the sample size, r is not close enough to 1 or -1 to say there is a linear correlation. B) since we can't prove there is a correlation, there is not a predictive equation. We should ignore the output for intercept and slope and consider it invalid for an equation. C) when you view the the scatter plot, it is either a curvilinear pattern or there is no pattern. D) All of the options are true.

D) All of the options are true.

A study comparing package weight (x) to the cost of shipping (y). The Excel Data Analysis Regression output is as follows: Multiple R0.90607 R Square0.820963 Adjusted R Square0.811017 Standard Error2.420018 Observations20 Given this, we can say: Question options: A) Approximately 91 percent of the variation in package weight (y) can be explained by knowing the shipping cost (x). B) Approximately 91 percent of the variation in shipping cost (y) can be explained by knowing the package weight (x). C) Approximately 82 percent of the variation in package weight (y) can be explained by knowing the shipping cost (x). D) Approximately 82 percent of the variation in shipping cost (y) can be explained by knowing the package weight (x).

D) Approximately 82 percent of the variation in shipping cost (y) can be explained by knowing the package weight (x).

In analyzing the relationship between two numeric variables, a scatter plot can be used to detect which of the following? A) A positive linear relationship B) A curvilinear relationship C) A negative linear relationship D) No apparent pattern in the scattered points E) All of the options are true

E) All of the options are true

A correlation coefficient (r) of -0.9 indicates a weak linear relationship between the variables. Question options:A) TrueB) False

False

Given the following sample: Order Total $(x)Tip Amount $(y)9.211.5017.823.7525.855.0032.766.5039.438.0047.329.0073.4615.0088.4518.00 Is it okay to use the regression equation for x values smaller than $9 and more than $89? Question options:A) TrueB) False

False

If the R-squared value for a regression model is high, the regression model will necessarily provide accurate forecasts of the y variable. Question options:A) TrueB) False

False

If two variables are highly correlated, it not only means that they are linearly related, it also means that a change in one variable will cause a change in the other variable. Question options:A) TrueB) False

False

In developing a scatter plot, it is proper to draw lines between all the points. Question options:A) TrueB) False

Flase

A correlation coefficient (r) is computed from a sample and is subject to sampling error. The hypothesis test to see if there the correlation coeffiecent is 0 (meaning no correlation) would use the greek r which is represented as � (rho) when writing Ho and Ha. Question options:A) TrueB) False

True

If the coefficient of determination is .45, this can be interpreted as 45% of the variation in the y-variable can be explained by knowing the x-variable. Question options:A) TrueB) False

True

The coefficient of determination (R Square) is always found by taking the correlation coefficient (r) and squaring it. Question options:A) TrueB) False

True

The following regression model has been computed based on a sample of twenty observations: y = 34.2 + 19.3x Given this model, the predictive model for y when x=40 is 806.2. Question options:A) TrueB) False

True

The results of a regression analysis indicate: WeeklySales$(y) = $1242 + $2.32 * Ad$Spent(x) Is it true that the equation tells us that for every $1 increase in Ad$Spent, the WeeklySales$ increases by $2.32? Question options:A) TrueB) False

True

When constructing a scatter plot, the dependent variable (what we are trying to predict) is placed on the vertical y-axis and the independent variable is placed on the horizontal x-axis. Question options:A) TrueB) False

True

When the slope in the regression equation is negative, the correlation coefficient (r) will always be negative. Question options:A) TrueB) False

True