A student calculates a linear model yy = xx + . (Please show your answers to two decimal places) Use the model to estimate the cost when number of pages is 496. Cost = $ (Please show your answer to 2 decimal places.)
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.
Statistics students in Oxnard College sampled 11 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below:
Number of Pages (xx) | Cost(yy) |
---|---|
615 | 40.75 |
268 | 32.4 |
501 | 43.05 |
268 | 30.4 |
731 | 56.55 |
508 | 41.4 |
493 | 38.65 |
964 | 60.2 |
650 | 43.5 |
332 | 30.6 |
261 | 27.05 |
A student calculates a linear model
yy = xx + . (Please show your answers to two decimal places)
Use the model to estimate the cost when number of pages is 496.
Cost = $ (Please show your answer to 2 decimal places.)
![](/static/compass_v2/shared-icons/check-mark.png)
Given Information:
Sample size (n) = 11
The data represents cost of 11 textbooks in the Condor bookstore and the number of pages in each book.
Linear model can be obtained using Excel:
Steps to follow are given below:
- Enter the data in Excel sheet
- Go to DATA-> Data Analysis
- Select Regression
- Enter Input Y range and input X range
- Check on labels
- Select the output Range and click ok
Excel output obtained is given below:
Step by step
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