Step
2 (A):
Having briefly examined the structure of the data,
now we take a deeper look at the relationship between the variables. Knowing
today's egg price per dozen, we first examine Egg Price and Cases. Take a
deeper look at Egg.Pr vs Cases: Fit a SLR
and create a data visualization with a fitted simple linear regression line.
Are there some noticeable outliers? If so also add a fitted SLR to the data
without including them to see if the line changes.
Question
3: Fill in the blank cells in the below table.
|
Estimate |
Std Error |
T value |
Pr( > |t| ) |
Intercept |
153414.5 |
15992.9 |
|
<< 0.0001 |
Egg.Pr |
|
168.2 |
|
|
Question
4: Write out the regression model and interpret the slope coefficient in
context.
Model: Slope interpretation: |
Question
5: Does it appear that prices of eggs is useful in predicting the current
week’s volume of egg sales? Explain your reasoning.
Answer: |
Question
6: What is the R2 value? Interpret this statistic.
Answer: |
Question
7: Create a data visualization with a fitted simple linear regression line. (1)
Are there some noticeable outliers? If so, also add a fitted SLR to the data
without including them to see if the line changes. (2) Finally, interpret your
final data visualization. Copy and paste your final visualization below.
Answer: (1) (2) |
Hints
Simple Linear Regression model helos to establish a relationship between two quantitative variables of which one variable is an independent variable
Coeficient helps to measure the extent of the effect that change in one ariable have on another. Slope coefficient denotes change in dependent variable as independent variable changes
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