Part 3: Data Distributions

Question 1

What is the non-linear transformation we apply to each value?

Moderate pos+ skewed data:

Substantially pos+ skewed data:

Severely pos+ skewed data:

Answer 1

Moderate pos+ skewed data:

Square root

Substantially pos+ skewed data:

Log (x)

Severely pos+ skewed data

1/x

Question 2

In a z-scores table, what are the z-scores for the upper and lower 5%?

Answer 2

-1.64 and +1.64

Question 3

What percentage or scores are within +/- 1.96 SD’s of the mean?

Answer 3

95%

Question 4

What percentage of scores are within +/- 2.58 SD’s of the mean?

Answer 4

99%

Question 5

95% of data lies within __ SD’s of the mean.

Answer 5

95% of data lies within 2 SD’s of the mean.

Question 6

How do we measure the extent to which a sample mean differs from the population mean?

I.e. The amount by which we are likely to error when estimating the population mean from the sample mean.

Answer 6

Compute the Standard Error of sample means.

Variance / square root of n.

Question 7

What are the 3 assumptions of the Central Limit Theorem?

Answer 7

1. The distribution of all sample means, will have a mean equal to the population mean.
2. The distribution of all means, will have a SD equal to the SE.
3. As the sample size (N) increases, the distribution of sample means will become closer to the population mean.

Question 8

In SPSS, the skewness statistic must be greater than __ to qualify for a non-linear transformation.

Answer 8

In SPSS, the skewness statistic must be greater than 2 to qualify for a non-linear transformation.