LEASE HELP ANSWER ALL SUBS G-i THANK YOU A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. PLAESE ANSWER ALL SUBS A-i its all one question Time 24 19 21 20 18 24 25 Money 102 78 79 80 72 84 105 A. Find the correlation coefficient: r= Round to 2 decimal places. The null and alternative hypotheses for correlation are: H0: ρ = 0 H1: ρ ≠ 0 B.The p-value is:? (Round to four decimal places) C. Use a level of significance of α=0.05 to state the conclusion of the hypothesis test in the context of the study? There is statistically insignificant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. There is statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful. There is statistically insignificant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the use of the regression line is not appropriate. D. r2 = (Round to two decimal places) E. Interpret r2? There is a 76% chance that the regression line will be a good predictor for the amount of money spent at the store based on the time spent at the store. There is a large variation in the amount of money that customers spend at the store, but if you only look at customers who spend a fixed amount of time at the store, this variation on average is reduced by 76%. Given any group that spends a fixed amount of time at the store, 76% of all of those customers will spend the predicted amount of money at the store. 76% of all customers will spend the average amount of money at the store. F. The equation of the linear regression line is: ˆy = + x (Please show your answers to two decimal places) G. Use the model to predict the amount of money spent by a customer who spends 20 minutes at the store. Dollars spent =. (Please round your answer to the nearest whole number.) H. Interpret the slope of the regression line in the context of the question? The slope has no practical meaning since you cannot predict what any individual customer will spend. For every additional minute customers spend at the store, they tend to spend on averge $4.01 more money at the store. As x goes up, y goes up. i. Interpret the y-intercept in the context of the question? The average amount of money spent is predicted to be $-0.71. If a customer spends no time at the store, then that customer will spend $-0.71. The best prediction for a customer who doesn't spend any time at the store is that the customer will spend -0.71. The y-intercept has no practical meaning for this study.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
PLEASE HELP ANSWER ALL SUBS G-i THANK YOU
A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below.
PLAESE ANSWER ALL SUBS A-i its all one question
| Time | 24 | 19 | 21 | 20 | 18 | 24 | 25 | ||
|---|---|---|---|---|---|---|---|---|---|
| Money | 102 | 78 | 79 | 80 | 72 | 84 | 105 |
A. Find the
The null and alternative hypotheses for correlation are:
H0: ρ = 0
H1: ρ ≠ 0
B.The p-value is:? (Round to four decimal places)
C. Use a level of significance of α=0.05 to state the conclusion of the hypothesis test in the context of the study?
- There is statistically insignificant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store.
- There is statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store.
- There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful.
- There is statistically insignificant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the use of the regression line is not appropriate.
D. r2 = (Round to two decimal places)
E. Interpret r2?
- There is a 76% chance that the regression line will be a good predictor for the amount of money spent at the store based on the time spent at the store.
- There is a large variation in the amount of money that customers spend at the store, but if you only look at customers who spend a fixed amount of time at the store, this variation on average is reduced by 76%.
- Given any group that spends a fixed amount of time at the store, 76% of all of those customers will spend the predicted amount of money at the store.
- 76% of all customers will spend the average amount of money at the store.
F. The equation of the linear regression line is:
ˆy = + x (Please show your answers to two decimal places)
G. Use the model to predict the amount of money spent by a customer who spends 20 minutes at the store.
Dollars spent =. (Please round your answer to the nearest whole number.)
H. Interpret the slope of the regression line in the context of the question?
- The slope has no practical meaning since you cannot predict what any individual customer will spend.
- For every additional minute customers spend at the store, they tend to spend on averge $4.01 more money at the store.
- As x goes up, y goes up.
i. Interpret the y-intercept in the context of the question?
- The average amount of money spent is predicted to be $-0.71.
- If a customer spends no time at the store, then that customer will spend $-0.71.
- The best prediction for a customer who doesn't spend any time at the store is that the customer will spend -0.71.
- The y-intercept has no practical meaning for this study.
Step-by-step procedure to draw the fitted line plot using Excel:
- In Excel sheet, enter and select Year in one column and enter Rate in one column.
- In Insert, select Scatter with only markers under Scatter.
- Right click the points in the graph and select Add trend line.
- Select Linear in Trend/Regression Type.
- Click Display Equation.
- Click Ok.
Output obtained using Excel is given below:
From the output, the linear regression equation is
G. The predicted amount of money spent by a customer who spends 20 minutes at the store is obtained below:
Thus, the amount of money spent by a customer who spends minutes at the store is 79
H. The slope of the regression line in the context of the question:
Answer:
Option.3. As x goes up, y goes up
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