Given are five observations for two variables, and . xi 1 3 12 15 17 yi 54 51 43 25 12 The estimated regression equation for these data is .
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.
Given are five observations for two variables, and .
xi | 1 | 3 | 12 | 15 | 17 |
yi | 54 | 51 | 43 | 25 | 12 |
The estimated regression equation for these data is .
![A tax preparation firm is interested in comparing the quality of work at two of its regional offices. The observed frequencies showing the number of sampled returns with errors and the
number of sampled returns that were correct are as follows.
Regional Office
Return
Office 1
Office 2
Error
35
28
Correct
217
274
a. What are the sample proportions of returns with errors at the two offices?
Office 1
Office 2
p (to 2 decimals)
b. Use the chi-square test procedure to see if there is a significant difference between the population proportion of error rates for the two offices. Test the null hypothesis H, : P1 = P2
with a .10 level of significance. What is the p-value?
Note: We generally use the chi-square test of equal proportions when there are three or more populations, but this example shows that the same chi-square test can be used for
testing equal proportions with two populations.
x²
(to 3 decimals)
The p-value is
- Select your answer - ♥
What is your conclusion?
Cannot conclude
that the two offices do not have the same population proportion error rates.
c. A X test statistic or a z test statistic may be used to test the hypothesis. However, when we want to make inferences about the proportions for two populations, we generally prefer
the z test statistic procedure. Comment on why the z test statistic provides the user with more options for inferences about the proportions of two populations.
With
populations, the test statistic X will always equal z*.
The chi-square test
v is preferred because it allows for two
v tailed tests.
The z-test
v is limited to
v tailed tests.
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