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The purpose of this exercise is to compare the variability of x1andx2 with the variability of (x1-x2).

a. Suppose the first sample is selected from a population with mean 1=150and variance 12=900. Within what range should the sample mean vary about 95%of the time in repeated samples of measurements from this distribution? That is, construct an interval extending standard deviations of x1on each side of 1 .

b. Suppose the second sample is selected independently of the first from a second population with mean 2=150 and variance22=1600 . Within what range should the sample mean vary about95% the time in repeated samples of 100 measurements from this distribution? That is, construct an interval extending standard deviationsx2 on each side2 .

c. Now consider the difference between the two sample means (x1-x2) . What are the mean and standard deviation of the sampling distribution(x1-x2) ?

d. Within what range should the difference in sample means vary about the 95%time in repeated independent samples of 100measurements each from the two populations?

e. What, in general, can be said about the variability of the difference between independent sample means relative to the variability of the individual sample means?

Short Answer

Expert verified

The standard deviation is a statistic that calculates the square root of the variance as well as quantifies the dispersal of a collection compared to its average.

Step by step solution

01

Central Limit Theorem.

According to theCentral Limit Theorem,the sampling distribution of the sample means approaches a normal distribution, irrespective of the shape of population distribution if the sample size is over 30.

02

(a) Find the interval extending standard deviations x1 on each side μ1 .

It is given that 1=150,12=900,n=100and confidence level is 95 % .

So, the confidence interval is 22n

=1502900100=15029=15023=1506

Therefore, the interval is from 144 to 156.

03

(b) Find the interval extending standard deviations x2 on each side μ2 .

It is given that2=150,22=1600,n=100 and confidence level is 95% .

So, the confidence interval is22n

=15021600100=150216=15024=1508

Therefore, the interval is from 142 to 158 .

04

(c) Find the mean and standard deviation of the sampling distribution (x¯1- x¯2).

It is given that 1=150,2=150,12=900,22=1600andn=100

x1-x2=1-2=150-150=0

x1-x2=12n1+22n2=900100+1600100=9+16=25=5

Therefore, the mean and standard deviation of the sampling distributionx1-x2 is 0 and 5 respectively.

05

(d) State the range within which the difference in sample means varies.

The difference in sample means will be normally distributed according to the Central Limit Theorem asn>30 .

06

(e) State the conclusion.

In general, we can say that the difference in sample means for independent sampling has variability equal to the sum of the individual variability of the means. It can be expressed as:

Ex1-x2=d=1-2

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Most popular questions from this chapter

A paired difference experiment produced the following results:

nd=38,x1=92,x2=95.5,d=-3.5,sd2=21

a. Determine the values zfor which the null hypothesis 12=0would be rejected in favor of the alternative hypothesis 12<0 Use .role="math" localid="1652704322912" 伪=.10

b. Conduct the paired difference test described in part a. Draw the appropriate conclusions.

c. What assumptions are necessary so that the paired difference test will be valid?

d. Find a90% confidence interval for the mean difference d.

e. Which of the two inferential procedures, the confidence interval of part d or the test of the hypothesis of part b, provides more information about the differences between the population means?

Question: The purpose of this exercise is to compare the variability of with the variability of .

a. Suppose the first sample is selected from a population with mean and variance . Within what range should the sample mean vary about of the time in repeated samples of measurements from this distribution? That is, construct an interval extending standard deviations of on each side of .

b. Suppose the second sample is selected independently of the first from a second population with mean and variance . Within what range should the sample mean vary about the time in repeated samples of measurements from this distribution? That is, construct an interval extending standard deviations on each side .

c. Now consider the difference between the two sample means . What are the mean and standard deviation of the sampling distribution ?

d. Within what range should the difference in sample means vary about the time in repeated independent samples of measurements each from the two populations?

e. What, in general, can be said about the variability of the difference between independent sample means relative to the variability of the individual sample means?

Shared leadership in airplane crews. Refer to the Human Factors (March 2014) study of shared leadership by the cockpit and cabin crews of a commercial airplane, Exercise 8.14 (p. 466). Recall that each crew was rated as working either successfully or unsuccessfully as a team. Then, during a simulated flight, the number of leadership functions exhibited per minute was determined for each individual crew member. One objective was to compare the mean leadership scores for successful and unsuccessful teams. How many crew members would need to be sampled from successful and unsuccessful teams to estimate the difference in means to within .05 with 99% confidence? Assume you will sample twice as many members from successful teams as from unsuccessful teams. Also, assume that the variance of the leadership scores for both groups is approximately .04.

Question: Consumers鈥 attitudes toward advertising. The two most common marketing tools used for product advertising are ads on television and ads in a print magazine. Consumers鈥 attitudes toward television and magazine advertising were investigated in the Journal of Advertising (Vol. 42, 2013). In one experiment, each in a sample of 159 college students were asked to rate both the television and the magazine marketing tool on a scale of 1 to 7 points according to whether the tool was a good example of advertising, a typical form of advertising, and a representative form of advertising. Summary statistics for these 鈥渢ypicality鈥 scores are provided in the following table. One objective is to compare the mean ratings of TV and magazine advertisements.

a. The researchers analysed the data using a paired samples t-test. Explain why this is the most valid method of analysis. Give the null and alternative hypotheses for the test.

b. The researchers reported a paired t-value of 6.96 with an associated p-value of .001 and stated that the 鈥渕ean difference between television and magazine advertising was statistically significant.鈥 Explain what this means in the context of the hypothesis test.

c. To assess whether the result is 鈥減ractically significant,鈥 we require a confidence interval for the mean difference. Although this interval was not reported in the article, you can compute it using the information provided in the table. Find a 95% confidence interval for the mean difference and interpret the result. What is your opinion regarding whether the two means are 鈥減ractically significant.鈥

Source: H. S. Jin and R. J. Lutz, 鈥淭he Typicality and Accessibility of Consumer Attitudes Toward Television Advertising: Implications for the Measurement of Attitudes Toward Advertising in General,鈥 Journal of Advertising, Vol. 42, No. 4, 2013 (from Table 1)

Predicting software blights. Relate to the Pledge Software Engineering Repository data on 498 modules of software law written in 鈥淐鈥 language for a NASA spacecraft instrument, saved in the train. (See Exercise 3.132, p. 209). Recall that the software law in each module was estimated for blights; 49 were classified as 鈥渢rue鈥 (i.e., the module has imperfect law), and 449 were classified as 鈥渇alse鈥 (i.e., the module has corrected law). Consider these to be Arbitrary independent samples of software law modules. Experimenters prognosticated the disfigurement status of each module using the simple algorithm, 鈥淚f the number of lines of law in the module exceeds 50, prognosticate the module to have a disfigurement.鈥 The accompanying SPSS printout shows the number of modules in each of the two samples that were prognosticated to have blights (PRED_LOC = 鈥測es鈥) and prognosticated to have no blights (PRED_LOC = 鈥渘o鈥). Now, define the delicacy rate of the algorithm as the proportion of modules. That was rightly prognosticated. Compare the delicacy rate of the algorithm when applied to modules with imperfect law with the delicacy rate of the algorithm when applied to modules with correct law. Use a 99-confidence interval.

DEFECT*PRED_LOC crosstabulation


PRED_LOC
total
noyes

DEFECT False

True

total

440

29

429

49

20

69

449

49

498

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