Given the following data set, 10 8 13 9 11 14 6 4 12 7 5 9.14 8.14 8.74 8.77 9.26 8.10 6.13 3.10 9.13 7.26 4.74 (a) Construct a scatter plot. (b) Find the value of the linear coefficient and then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. (c) Identify the feature of the data that would be missed if part (b) was completed without constructing the scatter plot.
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 the following data set,
|
10 |
8 |
13 |
9 |
11 |
14 |
6 |
4 |
12 |
7 |
5 |
|
|
9.14 |
8.14 |
8.74 |
8.77 |
9.26 |
8.10 |
6.13 |
3.10 |
9.13 |
7.26 |
4.74 |
(a) Construct a
(b) Find the value of the linear coefficient and then determine whether there is sufficient evidence to support the claim of a
(c) Identify the feature of the data that would be missed if part (b) was completed without constructing the scatter plot.
Using graphing calculator we shall plot the scattered plot.
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