To explain identify the True statement.

Question

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Answer 1

Question

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

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Students have asked these similar questions

14 A survey is conducted to determine whether would prefer to work at home, if given the 20 office employees of a certain company chance. The overall results are shown in the first bar graph, and the results broken down by gender are presented in the second. a. Interpret the results of each graph. b. Discuss the added value in including gen- der in the second bar graph. (The second bar graph in this problem is called a side by side bar graph and is often used to show results broken down by two or more variables.) c. Compare the side by side bar graph with the two pie charts that you made for Question 6. Which of the two methods is best for comparing two groups, in your opinion? A Would you prefer to work at home? (n=20) 60 50 40 Percent 20 30 20 30 10 0 No Yes Prefer to work at home? (10 males, 10 females) 80 Percent 60 00 40 40 20- No Yes No Yes Female Male

Frequency 12 Suppose that a random sample of 270 gradu- ating seniors are asked what their immediate priorities are, including whether buying a house is a priority. The results are shown in the following bar graph. a. The bar graph is misleading; explain why. b. Make a new bar graph that more fairly presents the results. Is Buying a House a Priority? 300 250 200 150 100 50 0 Yes No Undecided

Frequency 11 A polling organization wants to find out what voters think of Issue X. It chooses a random sample of voters and asks them for their opinions of Issue X: yes, no, or no opinion. I organize the results in the following bar graph. a. Make a frequency table of these results (including the total number). brocb. Evaluate the bar graph as to whether it biz s b fairly represents the results. of beau no STORE TO OW! vd wob spind 550 540 500 vd 480 420 360 300 250 240 Yes No Undecided Opinion on Issue X

Answer 2

Question

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

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Answer 3

Question

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

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Answer 4

Question

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

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Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 5

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

Answer 6

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.

Answer 7

Chapter 6, Problem 1PP

To determine

To explain identify the True statement.

Answer 8

Expert Solution & Answer

Answer to Problem 1PP

Statement A is true “Sampling bias increases the chance of committing Type 1 Error.”.

Answer 9

Expert Solution & Answer

Answer 10

Expert Solution & Answer

Answer 11

Explanation of Solution

Given:

The statements:

Sampling bias increases the chance of committing Type 1 Error.
There is no effect on probability of Type 1 Error due to sampling error.

Type 1 Error refers to the rejection of True null hypothesis. Which means a researcher rejects the null hypothesis when it is actually true. It is also known as the level of significance and it is denoted by α .

Factors that affect the chance of committing type 1 error are given below:

Sample Size
Level of significance

If the sampling error is higher means that the difference between estimated parameter and the true parameter are higher which means larger the value of test statistics and larger statistics value means lower the P value and P value is the maximum value of level of significance. Therefore, increase in sampling error implies decrease in the type 1 Error.

Therefore Option A is correct.