Incorrect practise test answers

Question 1

What is a discrete variable?

Answer 1

Any variables that can categorised OR put into countable values with meaningful intervals.

Question 2

What is a quasi-independent variable?

Answer 2

Independent variables that already exist but cannot be manipulated directly such as age or gender.

Question 3

Why are t statistics more variable than z-scores?

Answer 3

The extra variability is caused by variations in the sample variance.

Question 4

What do the values in the f column on a frequency table represent?

Answer 4

The amount of scores of a particular value (number of people with a particular X score for example).

Question 5

The mean can be considered a balance point for the distribution of scores: TRUE or FALSE.

Answer 5

TRUE.

Question 6

What symbol represents the deviation score?

Answer 6

(X-μ)

Question 7

What is the empirical rule (68%-95%-99.7% rule)?

Answer 7

A shorthand rule used to remember the percentage of values that lie within the standard deviations of normal distribution.

Question 8

What percent of values lie between the mean and the 1SD?

Answer 8

34%

Question 9

What percent of values lie between 1SD and 2SD?

Answer 9

13.5%

Question 10

What percent of values lie between 2SD and 3SD?

Answer 10

2.35%

Question 11

What is probability?

Answer 11

The extent to which an event is likely to occur, measured by the ratio of the favourable cases to the whole number of cases possible.

Question 12

What is generally considered an extreme score in a distribution?

Answer 12

Anything above or below 2SD.

Question 13

What is the numerator of a z-score?

Answer 13

(M-μ)

Question 14

What is the standard error formula? (σM)

Answer 14

σM = σ/√n

Question 15

How do you calculate the df for an independent measures t-test?

Answer 15

The df from group one plus the df from group two.
OR.
Add both groups and subtract 2.

Question 16

What is the formula for s(M₁ - M₂) and what is it’s major limitation?

Answer 16

s(M₁ - M₂) = the square root of s²/n₁ + s²/n₂.
(Each s² is for each sample).
CAN ONLY BE USED IF BOTH SAMPLES ARE THE SAME SIZE.

Question 17

What is the formula for s(M₁ - M₂) when samples are different sizes?

Answer 17

s(M₁ - M₂) = the square root of (pooled variance/n₁ + pooled variance/n₂).

Question 18

What does s(M₁ - M₂) represent?

Answer 18

Estimated standard distance between the difference in sample means (M₁ – M₂) and the difference in the corresponding population means (μ₁ – μ₂).

Question 19

What is the null hypothesis for an independent samples/measures t-test?

Answer 19

The two populations have equal means on some metric variable.