/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q8BSC In Exercises 5鈥8, use a signif... [FREE SOLUTION] | 91影视

91影视

In Exercises 5鈥8, use a significance level 0.05 and refer to theaccompanying displays.Cereal Killers The amounts of sugar (grams of sugar per gram of cereal) and calories (per gram of cereal) were recorded for a sample of 16 different cereals. TI-83>84 Plus calculator results are shown here. Is there sufficient evidence to support the claim that there is a linear correlation between sugar and calories in a gram of cereal? Explain.

Short Answer

Expert verified

There is enough evidence to support the claim that there exists a linear correlation between the two variables, sugar content and calories of the cereals.

Step by step solution

01

Given information

Two variables are being studied:the amount of sugar (grams of sugar per gram of cereal), and calories (per gram of cereal).

The sample size of cereals is 16(n).

The output gives the correlation coefficient as 0.7654038409.

02

Conduct a hypothesis test for correlation

Let\(\rho \)be the true correlation coefficient measure for the amount of sugar and calories.

For testing the claim, form the hypotheses as shown:

\(\begin{array}{l}{{\rm{H}}_{\rm{o}}}:\rho = 0\\{{\rm{{\rm H}}}_{\rm{a}}}:\rho \ne 0\end{array}\)

The samples number of cereals is16(n).

The test statistic is computedbelow:

\(\begin{aligned} t &= \frac{r}{{\sqrt {\frac{{1 - {r^2}}}{{n - 2}}} }}\\ &= \frac{{0.7654038409}}{{\sqrt {\frac{{1 - {{0.7654038409}^2}}}{{16 - 2}}} }}\\ &= 4.4501\end{aligned}\)

Thus, the test statistic is 4.450.

The degree of freedom is computedbelow:

\(\begin{aligned} df &= n - 2\\ &= 16 - 2\\ &= 14\end{aligned}\)

The p-value is computed using thet-distribution table.

\(\begin{aligned} p{\rm{ - value}} &= P\left( {T > t} \right)\\ &= 2P\left( {T > 4.4501} \right)\\ &= 2\left( {1 - P\left( {T < 4.4501} \right)} \right)\\ &= 0.0005\end{aligned}\)

Thus, the p-value is 0.0005.

03

State the conclusion

Since the p-value is lesser than 0.05, the null hypothesis is rejected.

Thus, there is enough evidence to support theexistence of a linear association between the amount of sugar (grams of sugarper gram of cereal)and calories (per gram of cereal).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Global Warming If we find that there is a linear correlation between the concentration of carbon dioxide (\(C{O_2}\)) in our atmosphere and the global mean temperature, does that indicate that changes in (\(C{O_2}\))cause changes in the global mean temperature? Why or why not?

Ages of Moviegoers Based on the data from Cumulative Review Exercise 7, assume that ages of moviegoers are normally distributed with a mean of 35 years and a standard deviation of 20 years.

a. What is the percentage of moviegoers who are younger than 30 years of age?

b. Find\({P_{25}}\), which is the 25th percentile.

c. Find the probability that a simple random sample of 25 moviegoers has a mean age that is less than 30 years.

d. Find the probability that for a simple random sample of 25 moviegoers, each of the moviegoers is younger than 30 years of age. For a particular movie and showtime, why might it not be unusual to have 25 moviegoers all under the age of 30?

Interpreting the Coefficient of Determination. In Exercises 5鈥8, use the value of the linear correlation coefficient r to find the coefficient of determination and the percentage of the total variation that can be explained by the linear relationship between the two variables.

Weight , Waist r = 0.885 (x = weight of male, y = waist size of male)

In Exercises 5鈥8, we want to consider the correlation between heights of fathers and mothers and the heights of their sons. Refer to theStatCrunch display and answer the given questions or identify the indicated items.

The display is based on Data Set 5 鈥淔amily Heights鈥 in Appendix B.

Identify the multiple regression equation that expresses the height of a son in terms of the height of his father and mother.

The following exercises are based on the following sample data consisting of numbers of enrolled students (in thousands) and numbers of burglaries for randomly selected large colleges in a recent year (based on data from the New York Times).

Enrollment (thousands)

53

28

27

36

42

Burglaries

86

57

32

131

157

True or false: If the sample data lead us to the conclusion that there is sufficient evidence to support the claim of a linear correlation between enrollment and number of burglaries, then we could also conclude that higher enrollments cause increases in numbers of burglaries.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.