CNSL 503 MODULE 3 FINAL TEST 2026
QUESTIONS WITH CORRECT ANSWERS
GRADED A+
◍ Hypothesis testing.
Answer: the formal process by which sample data is used to evaluate a
statistical hypothesis or a claim about a population (make inferences about a
population)-based on probability (it's not black and white), making a best
guess based on evidence from our sample
◍ response bias.
Answer: when participants respond in a way that is inaccurate or untruthful
◍ What are the four steps of hypothesis testing?.
Answer: 1 State the hypotheses (Ho and Ha) Ho= There is no relationship
between test scores and tutoring. (M= 75)Ha= There is a relationship
between test scores and tutoring. (M=X 75, M>75)2. Establish the decision
criteria (set the alpha level or significance level as 0.05)3. Collect data and
compute sample statistics as well as convert sample statistic into test statistic
(e.g. z-score)4. Make a decision (if p-value <= alpha level, reject the null
hypothesis, the result is statistically significant.)(if p value>= alpha level,
fail to reject the null hypothesis. there is no significant treatment effect).
◍ Identify the 4 steps in hypothesis testing..
Answer: State the null (H0) and alternative (Ha) hypotheses.Establish the
important cutoff (critical) values by which to measure the observed result to
determine statistical significance.Calculate the test statistic.Compare the test
statistic to the critical values, and decide if the null hypothesis (H0) should
be rejecting or not.
◍ What is a distribution of sample means?.
, Answer: a frequency distribution of all possible sample means.
◍ How to reduce the standard error?.
Answer: Increase the sample size! (with a larger n, the standard error is
smaller)
◍ Problems with Hypothesis Testing.
Answer: 1. Conventional levels of alpha (.05, .01, or .001) are arbitraryWe
just somehow decided, but probabilities exist on a continuum2. A larger
sample size is more likely to achieve statistical significance than a smaller
sample sizeStatistical significance does not always have meaningful
significanceEven small effects can be statistically significant with a large
enough sample size3 There is too much reliance on the p-value as the sole
measure upon which conclusions are madeConclusions should also be
drawn on past evidence, validity of assumptions made and so forth4 People
(including researchers!) misinterpret the p-value and the results of
hypothesis testing5 There is a bias towards publishing statistically
significant results over non-significant resultsThis leads to an incomplete
and biased picture of the findings
◍ 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.
◍ What is the purpose of a significance level?.
Answer: The significance level (α) is the value that the P-value of a test
statistic can be compared to in order to determine statistical significance.
This value is typically 0.05.
◍ What is the difference between a parameter and a statistic?.
Answer: A parameter is a numerical value that describes a population, such
as the population mean. A statistic is a numerical value that describes a
QUESTIONS WITH CORRECT ANSWERS
GRADED A+
◍ Hypothesis testing.
Answer: the formal process by which sample data is used to evaluate a
statistical hypothesis or a claim about a population (make inferences about a
population)-based on probability (it's not black and white), making a best
guess based on evidence from our sample
◍ response bias.
Answer: when participants respond in a way that is inaccurate or untruthful
◍ What are the four steps of hypothesis testing?.
Answer: 1 State the hypotheses (Ho and Ha) Ho= There is no relationship
between test scores and tutoring. (M= 75)Ha= There is a relationship
between test scores and tutoring. (M=X 75, M>75)2. Establish the decision
criteria (set the alpha level or significance level as 0.05)3. Collect data and
compute sample statistics as well as convert sample statistic into test statistic
(e.g. z-score)4. Make a decision (if p-value <= alpha level, reject the null
hypothesis, the result is statistically significant.)(if p value>= alpha level,
fail to reject the null hypothesis. there is no significant treatment effect).
◍ Identify the 4 steps in hypothesis testing..
Answer: State the null (H0) and alternative (Ha) hypotheses.Establish the
important cutoff (critical) values by which to measure the observed result to
determine statistical significance.Calculate the test statistic.Compare the test
statistic to the critical values, and decide if the null hypothesis (H0) should
be rejecting or not.
◍ What is a distribution of sample means?.
, Answer: a frequency distribution of all possible sample means.
◍ How to reduce the standard error?.
Answer: Increase the sample size! (with a larger n, the standard error is
smaller)
◍ Problems with Hypothesis Testing.
Answer: 1. Conventional levels of alpha (.05, .01, or .001) are arbitraryWe
just somehow decided, but probabilities exist on a continuum2. A larger
sample size is more likely to achieve statistical significance than a smaller
sample sizeStatistical significance does not always have meaningful
significanceEven small effects can be statistically significant with a large
enough sample size3 There is too much reliance on the p-value as the sole
measure upon which conclusions are madeConclusions should also be
drawn on past evidence, validity of assumptions made and so forth4 People
(including researchers!) misinterpret the p-value and the results of
hypothesis testing5 There is a bias towards publishing statistically
significant results over non-significant resultsThis leads to an incomplete
and biased picture of the findings
◍ 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.
◍ What is the purpose of a significance level?.
Answer: The significance level (α) is the value that the P-value of a test
statistic can be compared to in order to determine statistical significance.
This value is typically 0.05.
◍ What is the difference between a parameter and a statistic?.
Answer: A parameter is a numerical value that describes a population, such
as the population mean. A statistic is a numerical value that describes a
