1. Going Crackers! Do crackers with more fat content have greater energy content? Can knowing the percentage total fat content of a cracker help us to predict the energy content? If I switch to a different brand of cracker with 100mg per 100g less salt content, what change in percentage total fat content can I expect?

2. Going Crackers! Can knowing the percentage total fat content of a cracker help us to predict the energy content? Percentage total fat is the explanatory variable in this example. Energy is the response variable in this example.

3. Going Crackers! The energy content of 100g of cracker for 18 common cracker brands are shown in the dot plot with summary statistics below. 530480430380 Energy (Calories/100g) Common Cracker Brands VariableSample SizeMeanStd DevMinMaxLQUQ Energy18449.051.8375.5535.6407.3506.0

4. Going Crackers! Based on the information my prediction for the energy content of a cracker is ___________ calories per 100g. 530480430380 Energy (Calories/100g) Common Cracker Brands VariableSample SizeMeanStd DevMinMaxLQUQ Energy18449.051.8375.5535.6407.3506.0

5. Going Crackers! Based on the information my prediction for the energy content of a cracker is about 449 calories per 100g. 530480430380 Energy (Calories/100g) Common Cracker Brands VariableSample SizeMeanStd DevMinMaxLQUQ Energy18449.051.8375.5535.6407.3506.0

6. Going Crackers! Another quantitative variable which could be useful in predicting (the explanatory variable) the energy content (the response variable) of 100g of cracker is ______________________.

7. Going Crackers! Another quantitative variable which could be useful in predicting (the explanatory variable) the energy content (the response variable) of 100g of cracker is carbohydrate content.

8. Going Crackers! The Consumer magazine gives some nutritional information from an analysis of these 18 brands of cracker. Some of this information is shown in the table below: crackers data.xls

9. What do I see in these scatter plots? Response variable y-axis Explanatory variable x-axis

10. What do I see in these scatter plots? The data suggests a linear trend Positive association The data suggests constant scatter Appears to be a strong relationship No outliers No groupings

11. What do I see in these scatter plots?

12. The data suggests a linear trend Positive association The data suggests constant scatter Appears to be a moderate relationship No outliers No groupings

13. What do I see in these scatter plots?

14. No obvious trend overall Suggestion of two groups (about 30 or less AND about 50-60 crackers per pkt) No outliers

15. Going Crackers! From these plots, the best explanatory variable to use to predict energy content is _____________because _____________________________.

16. Going Crackers! From these plots, the best explanatory variable to use to predict energy content is total fat content because the relationship is stronger (less scatter) so I can make more reliable predictions.

17. Going Crackers! Roughly, my line predicts the energy content for a cracker with a 10% total fat content is about ______ Calories (per 100g of cracker).

18. Going Crackers! Roughly, my line predicts the energy content for a cracker with a 10% total fat content is about ______ Calories (per 100g of cracker).

19. Going Crackers! Roughly, my line predicts the energy content for a cracker with a 10% total fat content is about ______ Calories (per 100g of cracker).

20. Going Crackers! Roughly, my line predicts the energy content for a cracker with a 10% total fat content is about 440 Calories (per 100g of cracker).

21. Finding the equation of the fitted line Input the data for the crackers into your calculator crackers data.xls Make x variable total fat (List 3) Make y variable energy content (List 1) Graph Calculate stats crackers data.xlscrackers data.xls (fat graph)

22. Problem: How does the total fat content of a 100g of cracker change with a 100mg decrease in salt content? We have two quantitative variables, total fat content (%) and salt content (mg per 100g) measured on 18 common cracker brands. We are investigating the relationship between these two variables for the purpose of describing how the total fat content changes as the salt content changes.

23. Problem: How does the total fat content of a 100g of cracker change with a 100mg decrease in salt content? crackers data.xlscrackers data.xls (salt fat graph) The data suggests a linear trend. The association is positive and moderate. The data suggests constant scatter about the trend line. It is sensible to do a linear regression. crackers data.xlscrackers data.xls (salt fat analysis)

24. Problem: How does the total fat content of a 100g of cracker change with a 100mg decrease in salt content? The least squares line is or Predicted percentage fat content = -2.6556 + 0.0237  salt content. The slope of the fitted line is 0.0237 and the y-intercept is -2.6556. The regression equation says in crackers, on average, each 100mg decrease in salt content (per 100g) is associated with a decrease in the percentage total fat content by 2.4%. The moderate relationship (r = 0.69) means that predicting the percentage fat content of a brand of cracker from the salt content for that brand will not necessarily be highly accurate.