Consider the relationship between the number of bids an item on ebay received and the items selling price. The following is a sample of 5 items solf through an auction. Price in Dollars 20 21 21 35 44 Number of Bids 2 5 8 9 9 Summation Table X Y XY X2 Y2 Item 1 20 2 40 400 4 Item 2 21 5 105 441 25 Item 3 21 8 168 441 64 Item 4 35 9 315 1225 81 Item 5 44 9 396 1936 81 SUM 141 33 1024 4443 255 Step 1: Calculate the sum of squared errors (SSE). Use the values b0=0.9572 and b1=0.2001 for the calculations. Round your answer to three decimal places. Step 2: Calculate the estimated variance of errors, s2e. Step 3: Calculate the estimated variance of slope s2b1.
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.
Consider the relationship between the number of bids an item on ebay received and the items selling price. The following is a sample of 5 items solf through an auction.
|
Price in Dollars |
20 |
21 | 21 | 35 | 44 |
| Number of Bids | 2 | 5 | 8 | 9 | 9 |
Summation Table
| X | Y | XY | X2 | Y2 | |
| Item 1 |
20 |
2 | 40 | 400 | 4 |
| Item 2 | 21 | 5 | 105 | 441 | 25 |
| Item 3 | 21 | 8 | 168 | 441 | 64 |
| Item 4 | 35 | 9 | 315 | 1225 | 81 |
| Item 5 | 44 | 9 | 396 | 1936 | 81 |
| SUM | 141 | 33 | 1024 | 4443 | 255 |
Step 1: Calculate the sum of squared errors (SSE). Use the values b0=0.9572 and b1=0.2001 for the calculations. Round your answer to three decimal places.
Step 2: Calculate the estimated variance of errors, s2e.
Step 3: Calculate the estimated variance of slope s2b1.
Step 4: Construct the 80% confidence interval for the slope.
Lower endpoint:
upper endpoint:
Step 5: Construct the 90% confidence interval for the slope.
Lower endpoint:
upper endpoint:
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