week 11 hypothesis testing

Question 1

null hypothesis

Answer 1

no difference between relationship

Question 2

what does p-value tell us

Answer 2

how likely the obtained result would occur if the null hypothesis is true

Question 3

what are the standard levels to evaluate null hyp

Answer 3

0.05 and 0.01

Question 4

what is the difference between one tailed and two tailed test

Answer 4

one tailed is directional - for p<0.05, the specified side of null hyp must be p<0.05

two tailed is nondirectional - for p<0.05, each side of null hyp must be p<0.05

Question 5

how to write up the findings in APA format for a simple hypothesis on individual observations

Answer 5

“We can(not) conclude that the individual observation did not come from the population of (specified population)” followed by a comma then z equals your z value followed by a comma and p less than or equal to (value of p) or ns if not significant when hand calculation. Both z and p (ns) should be in italics.

Question 6

the steps of hypothesis testing under the normal distribution for individual observations.

Answer 6

First, state your null and experimental hypotheses.
Convert the individual observation into a Z-score. Recall, that z equals (x minus mu) over sigma.
Then compare your obtained value with the critical value of ±1.96. This is the critical value because only 5% of the scores in a distribution have a z-score with an absolute value greater than 1.96.
Next, you can make a statistical decision. If your obtained z-score is greater than ±1.96, you can reject the null hypothesis.
Finally, write up your results in APA format.

Question 7

recall what the central limit theorem states

Answer 7

if we obtain the sampling distribution of the mean from a population, the mean is equal to the population mean and a standard deviation equal to the standard error

Question 8

steps for simple hypotheses: Normal distribution for sample statistics (mean) when sigma is known

Answer 8

First, state your null and experimental hypotheses.
Next, compute the standard error. It is sigma divided by the square root of the sample size.
Convert the sample mean into a Z-score. Recall, that z equals (x bar minus mu) over sigma divided by the square root of the sample size.
Then compare your obtained value with the critical value of ±1.96. This is the critical value because only 5% of the scores in a distribution have a z-score larger than ±1.96.
Next, you can make a statistical decision. If your obtained (absolute) z-score is greater than ±1.96, you can reject the null hypothesis.
Finally, you can write-up your finding in APA format