Exam 14: Linear Correlation and Simple Linear Regression Analysis

Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, is analyzing household budget data collected by her firm. Abby's dependent variable is monthly household expenditures on groceries (in $'s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables: 11ea645c_71f3_c008_9252_276ec7aa4b76_TB1679_00 Using α = 0.05, Abby should ___.s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables: Using α = 0.05, Abby should ___." class="answers-bank-image d-inline" loading="lazy" > Using α = 0.05, Abby should ___.s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables: Using α = 0.05, Abby should ___." class="answers-bank-image d-inline" loading="lazy" > 11ea645c_71f3_c008_9252_276ec7aa4b76_TB1679_00 Using α = 0.05, Abby should ___.

From the following scatter plot, we can say that between Y and X there is ___.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch). The intercept of this model is the ___.

The first step in simple regression analysis usually is to construct a scatter plot.

A researcher has developed a regression model from fifteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two?tailed test and ɑ = 0.10. The critical table t value is ___.

A manager wishes to predict the annual cost (y) of an automobile based on the number of miles (x) driven. The following model was developed: y = 2,000 + 0.42x. If a car is driven 30,000 miles, the predicted cost is ___.

In the regression equation, y = 54.78 + 1.45x, the intercept is ___.

The range of admissible values for the coefficient of determination is −1 to +1.

The strength of a linear relationship in simple linear regression change if the units of the data are converted, say from feet to inches.

If x and y in a regression model are totally unrelated, ___.

Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables: For a lot size of 10,000 handsets, Louis' model predicts total cost will be ___.

Regression output from Excel software includes an ANOVA table.

A researcher has developed a regression model from 26 pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two? tailed test and ɑ = 0.01. The degrees of freedom for the critical table t value is ___.

Given x, a 95% prediction interval for a single value of y is always wider than a 95% confidence interval for the average value of y.

The assumptions underlying simple regression analysis include ___.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch). The slope of the accountant's model is ___.

One of the assumptions made in simple regression is that ___.

In the simple regression model, y = 21 − 5x, if the coefficient of determination is 0.81, we can say that the coefficient of correlation between y and x is 0.90.

A standard deviation of the error of the regression model is called the ___.

Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables: Louis's regression model is ___.