SCATTERPLOT

Chest is on the horizontal axis and Weight is on the vertical axis.

Step 2

The appears to be a linear correlation, because the points in the scatterplot lie roughly on a straight line.

asked 2021-06-03

Suppose you were to collect data for each pair of variables. You want to make a scatterplot. Which variable would you use as the explanatory variable and which as the response variable? Why? What would you expect to see in the scatterplot? Discuss the likely direction, form, and strength. Gasoline: number of miles you drove since filling up, gallons remaining in your tank

asked 2021-02-08

asked 2021-05-31

Suppose you were to collect data for each pair of variables. You want to make a scatterplot. Which variable would you use as the explanatory variable and which as the response variable? Why? What would you expect to see in the scatterplot? Discuss the likely direction, form, and strength. A streetlight: its apparent brightness, your distance from it.

asked 2021-06-28

Suppose you were to collect data for each pair of variables. You want to make a scatterplot. Which variable would you use as the explanatory variable and which as the response variable? Why? What would you expect to see in the scatterplot? Discuss the likely direction, form, and strength. Cars: weight of car, age of owner

asked 2021-06-08

Suppose you were to collect data for the pair of variables. You want to make a scatterplot. Which variable would you use as the explanatory variable and which as the response variable? Why? What would you expect to see in the scatterplot? Discuss the likely direction, form, and strength. College freshmen: shoe size, grade point average

asked 2021-05-31

x2761197642571339801278219008 y155314999328131667874116526 x2078219028143979606390525731 y267701652698686640122030730

The standardized residuals resulting from fitting the simple linear regression model (in the same order as the observations) are .98, -1.57, 1.47, .50, -.76, -.84, 1.47, -.85, -1.03, -.20, .40, and .81. Construct a plot of e* versus x and comment. [Note: The model fit in the cited article was not linear.]

asked 2021-05-18

Make a scatterplot for the data in each table. Use the scatter plot to identify and clustering or outliers in the data.
Value of Home Over Time
Number of Years Owned: 0, 3, 6, 9, 12, 15, 18, 21
Value (1,000s of $): 80, 84, 86, 88, 89, 117, 119, 86

asked 2021-02-08

asked 2021-06-26

Make a scatterplot of the data. Use 87 for 1987

.\(\begin{array}{|c|c|} \hline \text{ Year } & \text{ Sales (millions of dollars)} \\ \hline 1987 & 300 \\ \hline 1988 & 345 \\ \hline 1989 & 397 \\ \hline 1990 & 457\\ \hline 1991 & 510 \\ \hline 1992 & 578 \\ \hline 1993 & 664 \\ \hline 1994 & 700 \\ \hline 1995 & 770 \\ \hline 1996 & 792 \\ \hline 1997 & 830 \\ \hline 1998 & 872 \\ \hline 1999 & 915 \\ \hline \end{array}\)

asked 2021-05-07

Make a scatterplot of the data. Use 87 for 1987.

\( \begin{array}{|c|c|}\hline \text { Year } & {\text { Sales }} \\ & {\text { (millions of dollars) }} \\ \hline 1987 & {300} \\ \hline 1988 & {345} \\ \hline 1989 & {397} \\ \hline 1990 & {457}\\ \hline 1991 & {510} \\ \hline 1992 & {587} \\ \hline 1993 & {664} \\ \hline 1994 & {700} \\ \hline 1995 & {770} \\ \hline 1996 & {792} \\ \hline 1997 & {830} \\ \hline 1998 & {872} \\ \hline 1999 & {915} \\ \hline\end{array}\)