Could you teach me do this by Ti83or 84？ Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPT) and the cost of a slice of pizza We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice 0.15 0.35 1.00 1.25 1.75 2.00 of pizza () 1.) Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? 2.) Calculate the descriptive statistics. 3.) Calculate the sums of squares 4.) Calculate the slope, intercept and the correlation. What is this correlation value telling us? 5.) Assemble the prediction equation, and interpret the slope within the context of the problem. 6.) State the hypotheses for the hypothesis test for regression 7.) Fill in the ANOVA table below. Source df MS p-value Regression Error Total 8) What's your decision at a 5% significance level? Why? 9) State your conclusion. Do we have evidence of a relation between X and Y? Why or why not? 10.) Calculate the coefficient of determination (P). What does this tell us? 11.) In the year 2000, the CPI was 187.1. Predict the cost of a slice of pizza that year. Provide a prediction interval. Don't forget to make a concluding statement in the context of the problem. 12 ) Notice that the margin of error in the prediction interval is fairly high (about 25% of the point estimate) Why is this? What could we do to make our prediction more accurate? Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPT) and the cost of a slice of pizza We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice 0.15 0.35 1.00 1.25 1.75 2.00 of pizza () 1.) Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? 2.) Calculate the descriptive statistics. 3.) Calculate the sums of squares 4.) Calculate the slope, intercept and the correlation. What is this correlation value telling us? 5.) Assemble the prediction equation, and interpret the slope within the context of the problem. 6.) State the hypotheses for the hypothesis test for regression 7.) Fill in the ANOVA table below. Source df MS p-value Regression Error Total 8) What's your decision at a 5% significance level? Why? 9) State your conclusion. Do we have evidence of a relation between X and Y? Why or why not? 10.) Calculate the coefficient of determination (P). What does this tell us? 11.) In the year 2000, the CPI was 187.1. Predict the cost of a slice of pizza that year. Provide a prediction interval. Don't forget to make a concluding statement in the context of the problem. 12 ) Notice that the margin of error in the prediction interval is fairly high (about 25% of the point estimate) Why is this? What could we do to make our prediction more accurate?