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A researcher is interested in testing to determine if the mean price of a casual lunch is different in the city than it is in the suburbs. The null hypothesis is that there is no difference in the population means (i.e. the difference is zero). The alternative hypothesis is that there is a difference (i.e. the difference is not equal to zero). He randomly selects a sample of 9 lunch tickets from the city population resulting in a mean of $14.30 and a standard deviation of $3.40. He randomly selects a sample of 14 lunch tickets from the suburban population resulting in a mean of $11.80 and a standard deviation $2.90. He is using an alpha value of .10 to conduct this test. Assuming that the populations are normally distributed and that the population variances are approximately equal, the degrees of freedom for this problem are _______.

Sagot :

Answer:

The degrees of freedom for this problem are 21

Step-by-step explanation:

Degrees of freedom:

When testing an hypothesis involving two samples, the number of degrees of freedom is given by:

[tex]df = n_1 + n_2 - 2[/tex]

In which [tex]n_1[/tex] is the size of the first sample and [tex]n_2[/tex] is the sample of the second sample.

In this question:

Samples of 9 and 14, so [tex]n_1 = 9, n_2 = 14[/tex]

The degrees of freedom for this problem are

[tex]df = n_1 + n_2 - 2[/tex]

[tex]df = 9 + 14 - 2 = 21[/tex]

The degrees of freedom for this problem are 21

The required degree of freedom is 21.

Given that,

He randomly selects a sample of 9 lunch tickets from the city population resulting in a mean of $14.30 and a standard deviation of $3.40.

He randomly selects a sample of 14 lunch tickets from the suburban population resulting in a mean of $11.80 and a standard deviation $2.90.

He is using an alpha value of .10 to conduct this test.

We have to find,

The degrees of freedom for this problem are.

According to the question,

Degrees of freedom refers to the maximum number of logically independent values, which are values that have the freedom to vary, in the data sample.

Degrees of freedom are commonly discussed in relation to various forms of hypothesis testing in statistics, such as a chi-square.

When testing an hypothesis involving two samples, the number of degrees of freedom is given by,

[tex]Degree \ of \ freedom = n_1+n_2-2[/tex]

Where, [tex]n_1[/tex] is the size of the first sample and [tex]n_2[/tex] is the sample of the second sample.

[tex]n_1 = 9 \ and\ n_2 = 14[/tex]

Therefore,

[tex]Degree \ of \ freedom = 9+14-2\\\\Degree \ of \ freedom = 21[/tex]

Hence, The required degree of freedom is 21.

To know more about Degree of Freedom click the link given below.

https://brainly.com/question/23452965

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