Week Five

Question 1

descriptive statistics

Answer 1

• stats that simply describe statistics

- screen data and observe trends

Question 2

inferential statistics

Answer 2

• Use samples to infer something about a population.

- Allow us to test hypotheses and make decisions.

Question 3

unimodal

Answer 3

scores that vary around one point.

Question 4

modality

Answer 4

the number of central clusters that a distribution possesses

Question 5

bimodal

Answer 5

varies around two central points

Question 6

positive skew

Answer 6

tail points to right

Question 7

negative skew

Answer 7

tail points to left

Question 8

normal

Answer 8

• unimodal
• moderate peakness
• symmetric tails

Question 9

sum of squares

Answer 9

tell us about the total variability in the data set but does not characterise the degree by which each participant varies around the mean.
SS= sum of (X-M)^2

Question 10

variance

Answer 10

o^2= SS/(n-1)

Question 11

standard deviation

Answer 11

o= sqrt(SS/(n-1)).

essentially the average amount of variability around the mean.

Question 12

stat value

Answer 12

= estimate of effect size/estimate of error
compare the stat value against the appropriate probability distribution.
if it is far into the tails it is significantly different from the means.
= 0.05 or 0.001

Question 13

Z score

Answer 13

Z= (X-M)/SD

tells how many SDs away from the mean a particular score is.

Question 14

sample Z tests

Answer 14

for a population mean=100, SD=10, sample mean =104.75, n=20

Z= (M-u (pop))/Sm (SD/sqrt(n)).

Question 15

t tests

Answer 15

used where the pop mean is known but the SD is not.

t= (M-u)/(s(sqrt(SS/n-1)/ sqrt(n)).

Question 16

t

Answer 16

t distribution changes according to the size of the degrees of freedom.
this is because, the larger the sample, the more accurate our sample statistics estimate the population parameters.
- gets closer to normal as sample increases.
-slightly more error in t tests than z tests because the population variance is estimated and thus there is more distribution in the tails.

Question 17

df

Answer 17

= n-1

Question 18

repeated measures t test

Answer 18

identical to single sample but calculated from difference scores and u=0
Ho= no difference

Question 19

independent t test

Answer 19

two means from two different populations
t= (M1-M2)/Sdiff
sdiff= sqrt(s^2M1+S^2M2).

Question 20

single sample t test

Answer 20

comparing one set of data to the population

Question 21

t test assumptions

Answer 21

1. all observations are independent (ensure no participant’s performance is affected by or affects anothers).
2. distributions are normal (check histograms for skewness and kurtosis, samples over 30 - sample dist. is less important as theoretical distribution of the difference between the means will be normal).
3. homogeneity of variance
   - variance of one group is not too much larger than the other.
   - breaches to homogeneity can inflate type 1 error.