a. Calculate the slope and y-intercept for the linear regression equation for these data. b. Predict the demand for hot dogs on a day with a temperature of 10 degrees C.
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.
a. Calculate the slope and y-intercept for the linear regression equation for these data.
b. Predict the demand for hot dogs on a day with a temperature of 10 degrees C.
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![**Problem 14.3.17-T**
The following table shows the number of hot dogs bought from a street vendor over eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Complete parts a and b below.
| Temperature (°C) | 19 | 10 | 25 | 18 | 6 | 11 | 19 | 23 |
|------------------|----|----|----|----|---|----|----|----|
| Demand | 47 | 30 | 35 | 42 | 19| 22 | 43 | 35 |
**a. Calculate the slope and y-intercept for the linear regression equation for these data.**
\[ y = \boxed{}x + \boxed{} \]
(Round to two decimal places as needed.)
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