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The number of births per woman in China is 1.6down from 5.91in 1966. This fertility rate has been attributed to the law passed in 1979restricting births to one per woman. Suppose that a group of students studied whether or not the standard deviation of births per woman was greater than 0.75. They asked 50women across China the number of births they had had. The results are shown in Table. Does the students’ survey indicate that the standard deviation is greater than 0.75?

# of birthsFrequency0513021035

Short Answer

Expert verified

We do not reject the null hypothesis because the p-value is greater than the level of significance.

Step by step solution

01

Given Information

It is given that the number of births per woman in China is 1.6down from 5.91in 1966 and the data for the number of births by 50women is given.

Test whether the standard deviation of the number of births per woman in China is not greater than 0.75or not.

The null and alternative hypotheses are:

H0:σ=0.75

H1:σ>0.75

Therefore, the expected number of students to attend their graduation is 19.

02

Explanation

The calculation of mean and standard deviation is as shown below:

# of births(x)Frequency(f)x×fx2×f050013030302102040351545

Therefore, the mean and standard deviation will be calculated as:

x¯=∑fxn

=30+20+155+30+10+5

=1.3

s=∑x2fn-x¯2

=30+40+455+30+10+5-1.32

=0.61

The formula and calculation of the test statistic is:

χ2=(n-1)s2σ2

=(50-1)0.6120.752

=32.41

The degrees of freedom are 50-1=49. The formula and calculation of the p-value in Excel is:

Hence thep-value is0.9675

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Most popular questions from this chapter

A sample of 212commercial businesses was surveyed for recycling one commodity; a commodity here means any one type of recyclable material such as plastic or aluminum. Table 11.41shows the business categories in the survey, the sample size of each category, and the number of businesses in each category that recycle one commodity. Based on the study, on average half of the businesses were expected to be recycling one commodity. As a result, the last column shows the expected number of businesses in each category that recycle one commodity. At the 5% significance level, perform a hypothesis test to determine if the observed number of businesses that recycle one commodity follows the uniform distribution of the expected values.

Business
Type
Number in
class
Observed Number that recycles one commodityExpected number that recycles one commodity
office35
19
17.5
Retail/
Wholesale
48
27
24
Food/
Restaurants
53
35
26.5
Manufacturing/
Medical
52
21
26
Hotel/Mixed24
9
12

Table 11.41

The table provides a recent survey of the youngest online entrepreneurs whose net worth is estimated at one million dollars or more. Their ages range from 17to 30. Each cell in the table illustrates the number of entrepreneurs who correspond to the specific age group and their net worth. Are the ages and net worth independent? Perform a test of independence at the 5%significance level.

Age Groupl Net Worth Value (in millions of US dollars)1-56-24≥25Row Total17-258752026-3065920Column Total14121440

Determine the appropriate test to be used in the next three exercises.

An economist is deriving a model to predict outcomes on the stock market. He creates a list of expected points on the stock market index for the next two weeks. At the close of each day's trading, he records the actual points on the index. He wants to see how well his model matched what actually happened.

In general, if the observed values and expected values of a goodness-of-fit test are not close together, then the test statistic can get very large and on a graph will be way out in the right tail.

When looking at energy consumption, we are often interested in detecting trends over time and how they correlate among different countries. The information in Table 11.57 shows the average energy use (in units of kg of oil equivalent per capita) in the USA and the joint European Union countries (EU) for the six-year period 2005 to 2010. DoW? Perform the analysis at the 5% significance level.

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