Answered: What is the appropriate test to answer…

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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Question

Refer image to questions

-What is the appropriate test to answer this question?

-The null and alternative hypotheses are (choose from below)

H₀: π = 0.7, H₁: π ≠ 0.7

H₀: β = 0, H₁: β ≠ 0

H₀: μ = 0, H₁: μ ≠ 0

H₀: μ = 70, H₁: μ ≠ 70

H₀: μ₁- μ₂= 0, H₁: μ₁- μ₂ ≠ 0

- How can you justify the assumption for this test? (choose from below)

-Since nπ and n(1-π) are both ≥5, the Central Limit Theorem applies and we can assume that p arises from a normal distribution

-The shape of the histogram indicates that the scores may be from a normal distribution and/or the sample size is reasonably large so the sample mean will be from a normal population

-The boxplots indicate that the samples are fairly symmetric and the spreads are similar, so we can assume both sets of data come from normal distributions with the same spread

-The points are randomly scattered around a straight line, so the assumptions of linearity and constant spread are satisfied. The shape of the histogram indicates that the residuals come from a normal distribution

- None of these

- What is the value of the test statistic? (choose from below)

0.90938

1.833

18.818

0.04833

3.415

Notrun. Im<-1m(pulseB_NRSPulse2-pulseB_NR$Pulsel)
summary (Notrun. Im)
Before and After Pulse rates of Students who did not Run
Residuals; Students who Did not Run
-10
-5
10
60
70
80
90
resid(Notrun. Im)
Before Pulse Rate
call:
1m(formula
pulseB_NR$Pulse2
pulseB_NR$Pulsel)
coefficients:
Estimate
(Intercept)
pulseB_NR$Pulsel 0.90938
std. Error t value Pr(>|t|)
1. 833
0. 04833 18. 818
6. 52063
3.55765
0.0734
<2e-16
Residual standard error: 3.415 on 45 degrees of freedom
Multiple R-squared: 0.8872, Adjusted R-squared:
F-statistic: 354.1 on 1 and 45 DF, p-value: < 2.2e-16
0.8847
After Pulse Rate
06 08 02 09 09

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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