For the data given below, fill in the blanks, using Formulas, Descriptive Statistics and Regression outputs.Mean of X2:1)28th Percentile of X1:2)3)Standard Deviation of X2:4)YXIX210204007011304509712Median of X2:10350545)Correlation Between X1 and Y:Minimum value of X2:132037540146)3040065159)bo :2540094167)b,.3045053178)203003510)11)18SSR:103007519SSE:4030053ST:F Statistics:2012)Regression output203506413)14)21304506822Adjusted R Square:10400962315)MSE:30325542416)MSR:2517)Standard Error of Regression:18)19)20)26Standard error of X2:27t-statistics of X2:28Fit the regression equation:2930Sheet1

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Math

Statistics

For the data given below, fill in the blanks, using Formulas, Descriptive Statistics and Regression outputs.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

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.

Question

For the data given below, fill in the blanks, using Formulas, Descriptive Statistics and Regression outputs.
Mean of X2:
1)
28th Percentile of X1:
2)
3)
Standard Deviation of X2:
4)
Y
XI
X2
10
20
400
70
11
30
450
97
12
Median of X2:
10
350
54
5)
Correlation Between X1 and Y:
Minimum value of X2:
13
20
375
40
14
6)
30
400
65
15
9)
bo :
25
400
94
16
7)
b,.
30
450
53
17
8)
20
300
35
10)
11)
18
SSR:
10
300
75
19
SSE:
40
300
53
ST:
F Statistics:
20
12)
Regression output
20
350
64
13)
14)
21
30
450
68
22
Adjusted R Square:
10
400
96
23
15)
MSE:
30
325
54
24
16)
MSR:
25
17)
Standard Error of Regression:
18)
19)
20)
26
Standard error of X2:
27
t-statistics of X2:
28
Fit the regression equation:
29
30
Sheet1

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