1. What is the correlation coefficient (Pearson’s r) between the variable's calories and carb? 2. Interpret the strength of the relationship between the calories and the amount of carbohydrates (in grams) contained in the food menu at Starbucks. 3. Using JASP descriptive statistics, find the mean and standard deviation for the variable calories and carb
1. What is the correlation coefficient (Pearson’s r) between the variable's calories and carb? 2. Interpret the strength of the relationship between the calories and the amount of carbohydrates (in grams) contained in the food menu at Starbucks. 3. Using JASP descriptive statistics, find the mean and standard deviation for the variable calories and carb
1. What is the correlation coefficient (Pearson’s r) between the variable's calories and carb? 2. Interpret the strength of the relationship between the calories and the amount of carbohydrates (in grams) contained in the food menu at Starbucks. 3. Using JASP descriptive statistics, find the mean and standard deviation for the variable calories and carb
It is natural to think there will be a relationship between the number of calories and the amount of carbohydrates (in grams). In this journal, we will conduct a study using the nutrition data for several Starbucks food items. Click here for the dataset (spreadsheet) or Dataset (pdf)
Import the data to JASP, run the command and take a screenshot of your output. Based on that, answer the following questions.
1. What is the correlation coefficient (Pearson’s r) between the variable's calories and carb?
2. Interpret the strength of the relationship between the calories and the amount of carbohydrates (in grams) contained in the food menu at Starbucks.
3. Using JASP descriptive statistics, find the mean and standard deviation for the variable calories and carb
4. In a food label at Starbucks, the number of calories is indicated but the amount of carbohydrates (in grams) is missing. Write the equation of the regression line for prediction of the amount of carbohydrates (the response or dependent variables) given the number of calories (explanatory variable or covariate)
First calculate the slope (b_ 1).
Calculate the intercept (b_ 0).
Write the regression equation.
5. Using JASP linear regression, validate the regression equation found in c.
6. Calculate R2 of the regression line for predicting the amount of carbohydrates from the number of calories and interpret it in the context of the application.
Your submission of the Learning Journal assignment can be on a word document, a spreadsheet or a PDF.
Database PDF is attached via Images
Transcribed Image Text:The table shown provides nutritional information for various food items categorized under "bakery" and "bistro box" types. Each item includes measurements for calories, fat, carbohydrates, fiber, and protein.
### Key Components of the Table:
- **Columns:**
1. **Item**: Names of food items.
2. **Calories**: Total caloric content of each item.
3. **Fat**: Amount of fat in grams.
4. **Carb (Carbohydrates)**: Amount of carbohydrates in grams.
5. **Fiber**: Amount of dietary fiber in grams.
6. **Protein**: Amount of protein in grams.
7. **Type**: Category, either "bakery" or "bistro box."
- **Sample Rows Explained:**
- *8-Grain Roll*: Contains 350 calories, 8g fat, 67g carbs, 5g fiber, 10g protein, categorized as bakery.
- *Blueberry Scone*: Contains 460 calories, 22g fat, 61g carbs, 2g fiber, 7g protein, categorized as bakery.
- *Chicken & Hummus*: Contains 270 calories, 8g fat, 29g carbs, 6g fiber, 16g protein, categorized as bistro box.
- **Analysis:**
- Items range from low to high in calorie content, with the highest being "Cinnamon" at 480 calories.
- Bakery items tend to have higher carbohydrate content compared to bistro box items.
- Protein varies widely, with bistro box items generally providing more protein.
This table can serve as a useful guide for nutritional comparisons and for making informed dietary choices based on individual nutritional needs or preferences.
Definition Definition Statistical measure used to assess the strength and direction of relationships between two variables. Correlation coefficients range between -1 and 1. A coefficient value of 0 indicates that there is no relationship between the variables, whereas a -1 or 1 indicates that there is a perfect negative or positive correlation.
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