Probability

Question 1

what is usually displayed on the X axis?

Answer 1

the measured variable

Question 2

what is usually displayed on the Y axis?

Answer 2

the frequency

Question 3

what are the characteristics of a normal distribution graph?

Answer 3

• Naturally Occurring
• Asymptotic (theoretically)
• Symmetrical

Question 4

what is always in the middle of a distribution curve?

Answer 4

The mode, median and mean

Question 5

what percentage of data is in the 1st SD?

Answer 5

68.56% (34.13% either positive or negative)

Question 6

what percentage of data is in the 2nd SD?

Answer 6

34.13% (13.59% either positive or negative)

Question 7

what percentage of data is in the 3rd SD?

Answer 7

4.3% (2.15% either positive or negative)

Question 8

how do you determine the Z score?

Answer 8

average+SD

Question 9

characteristics of Non-Normal distribution graphs

Answer 9

asymmetrical
mode, median and mean are all in different areas of the graph
can either have a positive or negative skew

Question 10

why is distribution important?

Answer 10

• Determines which measure of central tendency to use
• Determines which measure of variability to use
• Provides ‘Z-score’ for standardised comparisons
• Determines further statistical analysis
• Parametric (assumes ND, random sample-more powerful)
• Non-parametric (simply calculated, distribution free-less powerful).

Question 11

probability can scale from either

Answer 11

0-1
or
0%-100%

Question 12

why do we need to understand probability?

Answer 12

• p-values are used in research and statistics!
• in order to determine how likely it is that:
• there is NO difference between groups /samples
• there is NO correlation between two variables

Question 13

why do we use inferential stats?

Answer 13

1. objectively interpret data
2. Make an ‘inference’ about a population from our research sample
3. draw conclusions

Question 14

sample means can either be:

Answer 14

•‘real’:
-indicative of a difference between the 2 populations
•numerical only
-a ‘chance’ finding
-there is no difference between the 2 populations, just between the 2 samples

Question 15

what does the null-hypothesis state?

Answer 15

•there is no difference in the population

Question 16

•If H0 is correct:

Answer 16

• i.e.: no real difference between the two populations

* any observed NUMERICAL difference is coincidental

Question 17

what will happen to the probability if the null-hypothesis is true?

Answer 17

We can calculate the probability (p): of finding a result as big or bigger as the one we observed, if the null hypothesis is true

Question 18

why test the null-hypothesis?

Answer 18

• Null hypothesis is always exact (i.e.: REAL difference = 0)
• We are rarely able to exactly predict how big the difference should be for the experimental hypothesis
• Statistically we can work out the probability of finding a difference similar to or larger than we observed if H0 is correct
• If this probability is low enough, we reject H0 and accept that there is (probably) a real difference

Question 19

when do we reject the probability?

Answer 19

We reject the null hypothesis if the probability of finding a similar or larger difference by chance is less than 5%

Question 20

procedure: if p<0.05 we conclude that:

Answer 20

• the probability of finding a similar or larger difference is low enough to reject H0
• there is a SIGNIFICANT difference

Question 21

procedure: if p>0.05 we conclude that:

Answer 21

• the probability of finding a similar or larger difference is too high to be able to reject H0
• there is no SIGNIFICANT difference