Question

3. The following table shows data for the cost of natural gas in Maryland (in dollars per Million Btu) for x years since 1990, values in x cokimin. Define the explanatory and response variables for this problem in complete sentences. (3pts) The explanatory variable is the year and the response variable is the price per million Btu. a b. Use the Statkex (2quantitative variables) or calculator to obtain the linear regression line of best fit for the original prices, round to three decimal places. (3pts) Write the prediction equation in the form: 9 = ax +b below Y=5.574+0.356*x USE THIS as XO Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 1 2 3 4 5 6 7 8 9 10 11 12 Price in $ per Million Btu, y 6.28 6.01 6.26 6.89 6.75 6.45 7.39 8.09 8.00 8.14 9.47 11.24 9.27 interpret the slope in the context of the problem. (3pts)

Answer 1

Copy the given data into STATKEY software.

StatKey Descriptive Statistics for Two Quantitative Variables Custom Dataset - Show Data Table Edit Data Upload File Chamo Summary Statistics Saulich Variables 11.0 Statistic Y 6.000 3.894 1.547 10.0 Standard Deviation Sample Correlation Slope Intercepe 0.396 9.0 Scatterplot Controls Show Regression Line 8.0 7,0 6.0 O 10 Help SeatKey 2.1.1 written in Jocere and should work well with my current browser including Creme Fleefox. Safet Gere, and E. Comments, feedback, and bug reports can be sent to lock statepail.com Prati OR

From above figure, intercept = 5.574 and slope = 0.356

Hence, the regression line of Y on X will be,

  $\hat{Y}=5.574 + 0.356 X$

Here, we see a positive correlation between Y and X, which means that the Price in $ per million (Y)  increases with Year(X)

Interpretation of slope: If the Year incrases by 1, then model predicts that the Price in $ per million will increase by 0.356.