It has been hypothesized that there is some kind of relationship between the average daily temperature and the number of road injuries brought to a capital hospital. The dataset attached here presents the values of both variables. The Dataset 1 corresponds to the Temperature. Data 1 Data 2 11 28 20 39 37 47 42 57 52 69 69 77 Required: 1. Draw a scatterplot. 2. Calculate the Value of Pearson's Product Movement Correlation Coefficient. 3. State the hypotheses for Correlation.
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.
It has been hypothesized that there is some kind of relationship between the average daily temperature and the number of road injuries brought to a capital hospital. The dataset attached here presents the values of both variables. The Dataset 1 corresponds to the Temperature.
| Data 1 | Data 2 |
| 11 | 28 |
| 20 | 39 |
| 37 | 47 |
| 42 | 57 |
| 52 | 69 |
| 69 | 77 |
Required:
1. Draw a
2. Calculate the Value of Pearson's Product Movement
3. State the hypotheses for Correlation.
4. Test the significance of Correlation at Alpha = 0.05, using Table 1.
5. Describe the relationship between both variables.
6. Find the equation of the regression line.
7. What is your estimation of the number of patients arriving on a day when the temperature is 25 degrees?
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