Central limit theorem and hypothesis testing

Question 1

According to Central Limit Theorem the mean of a random sample will more closely resemble the mean of the whole population and the same size increases . True / False?

Answer 1

TRUE - regardless of the shape of distribution

Question 2

Central limit theorem describes the distribution of sample means by identifying 3 basic characteristics to describe any distribution what are they?

Answer 2

Shape
central tendency ( mean )
variability

Question 3

The distribution is almost perfectly normal if either of the following 2 conditions are met

Answer 3

1. population from which the samples are selected is a normal distribution
2. The no of scores in each sample is large around 30 or more

Question 4

As the sample size increase the spread of the means ( variability ) becomes larger? True / False

Answer 4

FALSE the spread of the means becomes smaller as sample size increases ( closer to bell curve

Question 5

Standard Deviation is?

Answer 5

distance between raw score and sample mean

Question 6

Standard error is?

Answer 6

the standard distance between a sample mean and the population mean

Question 7

What is statistical power?

Answer 7

The probability that it will reject a false null hypothesis. The likelihood that a study will detect an effect when there is an effect to be detected.

Question 8

What level of statistical power is acceptable?

Answer 8

In psychology 0.80 power is the minimum acceptable level. This means there is only a 20% chance of making a type 2 error.

Question 9

Can a study have too much power?

Answer 9

Yes! if its too high the tiniest effect will be deemed significant. This is why researchers need to report the effect size as well as the alpha level.

Question 10

How can researchers improve power if there is not enough?

Answer 10

Increase sample size or increase effect size by providing stronger treatment effect.