CNSL503 / CNSL 503 Module 3:
(Latest Update )
Statistics | Questions and Answers |
Grade A | 100% Correct - Portage
Learning
Question:
What is the difference between the null and alternative hypotheses?
Answer:
The null hypothesis (H0) is the beginning assumption of any hypothesis test
that makes a particular claim about the value of a population parameter and,
in essence, claims that an observed effect or difference does not exist. The
alternative hypothesis (Ha) states that the value of the population parameter
differs from the value claimed in the null hypothesis and, in essence, claims
that an observed result or difference does exist.
Question:
Distribution of sample means
Answer:
Refers to a sample statistic distribution that contains the frequencies of the
means of all possible samples of a given size from a population
, Question:
What is the difference between Type I and Type II errors?
Answer:
Type I errors are false positives
Type II errors are false negatives.
Question:
Identify the 4 steps in hypothesis testing
Answer:
1. State the null (H0) and alternative (Ha) hypotheses.
2. Establish the important cutoff (critical) values by which to measure the
observed result to determine statistical significance.
3. Calculate the test statistic.
4. Compare the test statistic to the critical values, and decide if the null
hypothesis (H0) should be rejecting or not.
(Latest Update )
Statistics | Questions and Answers |
Grade A | 100% Correct - Portage
Learning
Question:
What is the difference between the null and alternative hypotheses?
Answer:
The null hypothesis (H0) is the beginning assumption of any hypothesis test
that makes a particular claim about the value of a population parameter and,
in essence, claims that an observed effect or difference does not exist. The
alternative hypothesis (Ha) states that the value of the population parameter
differs from the value claimed in the null hypothesis and, in essence, claims
that an observed result or difference does exist.
Question:
Distribution of sample means
Answer:
Refers to a sample statistic distribution that contains the frequencies of the
means of all possible samples of a given size from a population
, Question:
What is the difference between Type I and Type II errors?
Answer:
Type I errors are false positives
Type II errors are false negatives.
Question:
Identify the 4 steps in hypothesis testing
Answer:
1. State the null (H0) and alternative (Ha) hypotheses.
2. Establish the important cutoff (critical) values by which to measure the
observed result to determine statistical significance.
3. Calculate the test statistic.
4. Compare the test statistic to the critical values, and decide if the null
hypothesis (H0) should be rejecting or not.
