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Two independent random samples were selected from normally distributed populations to conduct an experiment on the variability of responses of two different experimental procedures that may or may not be the same. The sample sizes, means, and variances are shown in the following table

a. Test the null hypothesis\({H_0}:{\mu _d} = 0\)against\({H_0}:{\mu _d} \ne 0\), where,\({\mu _d} = {\mu _1} - {\mu _2}\). Compare\(\alpha = 0.05\)with the p-value of the test

Short Answer

Expert verified

we fail to reject the null hypothesis.

Step by step solution

01

Given Information

The sample sizes are 14 and 16

The means are 44 and 41.

The variances are 569.2 and 810

The hypothesis are given by

\(\begin{aligned}{l}{H_0}:{\mu _d} = 0\\{H_a}:{\mu _d} \ne 0\end{aligned}\)

02

Test statistic

For

\(\begin{aligned}{l}{n_1} &= 14,\,\,{n_2} &= 16\\{{\bar x}_1} = 44,\,\;{{\bar x}_2} &= 41\\s_1^2 &= 569.2,\,s_2^2 &= 810\end{aligned}\)

The test statistic is computed as

\(\begin{aligned}{c}t &= \frac{{\left( {{{\bar x}_1} - {{\bar x}_2}} \right) - {D_0}}}{{\sqrt {\frac{{s_1^2}}{{{n_1}}} + \frac{{s_2^2}}{{{n_2}}}} }}\\ &= \frac{{\left( {44 - 41} \right) - 0}}{{\sqrt {\frac{{569.2}}{{14}} + \frac{{810}}{{16}}} }}\\ &= \frac{3}{{\sqrt {40.65 + 50.62} }}\\ &= \frac{3}{{9.55}}\\ = 0.314\end{aligned}\)

Therefore, the test statistic is 0.314.

03

P-value

Degrees of freedom are calculated as

\(\begin{aligned}{c}df &= {n_1} + {n_2} - 2\\ &= 14 + 16 - 2\\ = 30 - 2\\ &= 28\end{aligned}\)

For \(df = 28,\alpha = 0.05\,and\,t = 0.314\)

The p-value is 0.755.

Here, the p-value is greater than 0.05. Therefore, we fail to reject the null hypothesis.

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Most popular questions from this chapter

Assume that x is a binomial random variable with n = 1000 andp = 0.50. Use a normal approximation to find each of the following probabilities:

a. P(x>500)

b.P(490โ‰คx<500)

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Question: Deferred tax allowance study. A study was conducted to identify accounting choice variables that influence a managerโ€™s decision to change the level of the deferred tax asset allowance at the firm (The Engineering Economist, January/February 2004). Data were collected for a sample of 329 firms that reported deferred tax assets in 2000. The dependent variable of interest (DTVA) is measured as the change in the deferred tax asset valuation allowance divided by the deferred tax asset. The independent variables used as predictors of DTVA are listed as follows:

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EARN: x5 = change in operating earnings divided by total assets

A first-order model was fit to the data with the following results (p-values in parentheses):

Ra2 = .280

y^=0.044+0.006x1-0.035x2-0.001x3+0.296x4+0.010x5

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  1. Interpret the estimate of the ฮฒ coefficient for x4.
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Question: The speed with which consumers decide to purchase a product was investigated in the Journal of Consumer Research (August 2011). The researchers theorized that consumers with last names that begin with letters later in the alphabet will tend to acquire items faster than those whose last names begin with letters earlier in the alphabetโ€”called the last name effect. MBA students were offered free tickets to an event for which there was a limitedsupply of tickets. The first letter of the last name of those who responded to an email offer in time to receive the tickets was noted as well as the response time (measured in minutes). The researchers compared the response times for two groups of MBA students: (1) those with last names beginning with one of the first nine letters of the alphabet and (2) those with last names beginning with one of the last nine letters of the alphabet. Summary statistics for the two groups are provided in the table.

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25

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Source: Based on K. A. Carlson and J. M. Conrad, โ€œThe Last Name Effect: How Last Name Influences Acquisition Timing,โ€ Journal of Consumer Research, Vol. 38, No. 2, August 2011.

a. Construct a 95% confidence interval for the difference between the true mean response times for MBA students in the two groups.

b. Based on the interval, part a, which group has the shorter mean response time? Does this result support the researchersโ€™ last name effect theory? Explain.

Whistle-blowing among federal employees. Whistle blowing refers to an employeeโ€™s reporting of wrongdoing by co-workers. A survey found that about 5% of employees contacted had reported wrongdoing during the past 12 months. Assume that a sample of 25 employees in one agency are contacted and let x be the number who have observed and reported wrongdoing in the past 12 months. Assume that the probability of whistle-blowing is .05 for any federal employee over the past 12 months.

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