a) To the left of a z-score of 1.25

b) To the right of a z-score of 1.25

c) Between the z-scores -0.25 and 0.55

alesterp
2021-11-06
Answered

Using the Standard Normal Table from the online lectures this week, what is the area under the standard normal curve:

a) To the left of a z-score of 1.25

b) To the right of a z-score of 1.25

c) Between the z-scores -0.25 and 0.55

a) To the left of a z-score of 1.25

b) To the right of a z-score of 1.25

c) Between the z-scores -0.25 and 0.55

You can still ask an expert for help

sovienesY

Answered 2021-11-07
Author has **89** answers

Step 1

To the left of Z score of 1.25 from Standard Normal probability table,

from Standard Normal probability table,

z row 1.2 and z column 0.05 the value is 0.8944

Hence

Step 2

To the right of Z score of 1.25

from Standard Normal probability table,

z row 1.2 and z column 0.05 the value is 0.8944

Hence

Step 3

Between the Z-Scores -0.25 and 0.55

from Standard Normal probability table,

z row 0.2 and z column 0.05 the value is 0.5987

z row 0.5 and z column 0.05 the value is 0.7088

Hence

asked 2020-11-01

Round each z-score to the nearest hundredth.

A data set has a mean of

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A data set has a mean of

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A survey was conducted to investigate the relationship between gender (male and females) and sector of employment (private, government and academia). Using the information provided, does a relationship exist between gender and employment sector at the 5% significance level? If the Chi-square test statistics = 0.529, what conclusion can be made?

A. Since Chi-square test statistics > Chi-square critical value, do not reject$H}_{0$

B. Since Chi-square test statistics < Chi-square critical value, do not reject$H}_{0$

C. Since Chi-square test statistics < Chi-square critical value, Reject$H}_{0$

D. Since Chi-square test statistics > Chi-square critical value, Reject$H}_{0$

A. Since Chi-square test statistics > Chi-square critical value, do not reject

B. Since Chi-square test statistics < Chi-square critical value, do not reject

C. Since Chi-square test statistics < Chi-square critical value, Reject

D. Since Chi-square test statistics > Chi-square critical value, Reject

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asked 2022-06-24

What is a 'critical value' in statistics?

The raw material needed for the manufacture of medicine has to be at least $97\mathrm{\%}$ pure. A buyer analyzes the nullhypothesis, that the proportion is ${\mu}_{0}=97\mathrm{\%}$, with the alternative hypothesis that the proportion is higher than $97\mathrm{\%}$. He decides to buy the raw material if the nulhypothesis gets rejected with $\alpha =0.05$. So if the calculated critical value is equal to ${t}_{\alpha}=98\mathrm{\%}$, he'll only buy if he finds a proportion of $98\mathrm{\%}$ or higher with his analysis. The risk that he buys a raw material with a proportion of $97\mathrm{\%}$ (nullhypothesis is true) is $100\times \alpha =5\mathrm{\%}$

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asked 2021-12-13

Here are summary statistics fro randomly selected weights of newborn girs:

$n=240,\text{}\stackrel{\u2015}{x}=26.1hg,\text{}s=6.3hg$

Construct a confidence interval estimate of the mean. Use a$99\mathrm{\%}$ confidence level. Are these results very different from the confidence interval

$25.1hg<\mu <28.1hg$

with only 13 sample values,

$\stackrel{\u2015}{x}=26.6hg$ and $s=1.8hg?$

What is the confidence interval for the population mean$\mu ?$

Are the results between the two confidence intervals very different?

a) No, because each confidence interval contains the mean of the other confidence interval.

b) No, because the confidence interval limits are similar.

c) Yes, because the confidence interval limits are not similar.

d) Yes, because one confidence interval does not contain the mean of the other confidence interval.

Construct a confidence interval estimate of the mean. Use a

with only 13 sample values,

What is the confidence interval for the population mean

Are the results between the two confidence intervals very different?

a) No, because each confidence interval contains the mean of the other confidence interval.

b) No, because the confidence interval limits are similar.

c) Yes, because the confidence interval limits are not similar.

d) Yes, because one confidence interval does not contain the mean of the other confidence interval.