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A level psychology > Inferential statistics > Flashcards

Inferential statistics Flashcards

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1
Q

What are inferential statistics?

A

Tests applied to data to work out whether the null hypothesis or alternative hypothesis was supported
Allows us to draw conclusions

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2
Q

Accepting the alternative hypothesis

A

The data found that the IV had a significant effect on the DV
because there was a significant difference between data scores of conditions with IV, and without the IV

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3
Q

Accepting the null hypothesis

A

The data found the IV had no significant effect on DV and any differences were due to chance
No significant difference between scores of condition with IV and scores of conditions without the IV

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4
Q

2 types of Inferential statistic test

A

Parametric (powerful)
Non parametric (less powerful)

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5
Q

What does the non parametric test that we use on a data set depend on?

A

Experimental design
Level of data

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6
Q

what test do we use for Nominal level data from an independent measures experiment?

A

Chi square test

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7
Q

what test do we use for Nominal level data from a repeated measures/ matched participant experiment?

A

Binomial sign test

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8
Q

what test do we use for ordinal level data from an independent measures experiment?

A

Mann-Whitney U test

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9
Q

Why is there no test for nominal level data from a correlation study?

A

Nominal data is headcounts so data can’t be put on a scale thus cannot be used for a correlation study

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10
Q

what test do we use for ordinal level data from a repeated measures/ matched participant experiment?

A

Wilcoxon signed ranks test

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11
Q

What test do we use when we have ordinal level data from a correlation study?

A

Spearman’s Rho correlation coefficient

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12
Q

3 criteria for when we use a parametric test

A

Data is interval or ratio
It has a normal distribution curve
The variances of each conditions’ data are similar (similar distribution around mean)

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13
Q

Level of significance

A

The level at which the difference between 2 values are found to be statistically significant
SO there is a low probability that the differences are due to chance

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14
Q

p value

A

The probability found that the results are due to chance

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15
Q

Type 1 error

A

false positive error = falsely claimed to have found significant difference
They found the probability results were due to chance was lower than reality: lower than level of significance allowing them to make false claim

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16
Q

Type 1 error in terms of accepting/rejecting hypothesis

A

falsely accepted alternative hypothesis when they should have rejected it
Should have accepted null hypothesis

17
Q

Type 2 error

A

false negative error = falsely claimed to have found no significant difference when there was one
Found probability the results were due to chance to be larger than reality: higher than level of significance allowing them to make false negative claim

18
Q

Type 2 error in terms of accepting/rejecting hypothesis

A

falsely accepted null hypothesis when they should have rejected it
falsely rejected alternative hypothesis when they should have accepted it

19
Q

How to remember difference between type 1 and 2 errors

A

Type 1 error = person boastful about getting number 1 when they shouldn’t
Type 2 error = person who always puts themselves second wrongly when they shouldn’t

20
Q

Distribution curves

A

A type of graph with a (distorted or bell shaped) curve that data about a behaviour from a sample will fall around: shows the data’s distribution and range

21
Q

Peak of all distribution curves

A

The mode = scores the most number of participants achieved

22
Q

Types of distribution curves

A

Normal distribution
Positively skewed distribution
Negatively skewed distribution

23
Q

As you move away from the mode on a distribution curve what happens?

A

Fewer and fewer participants scored these values

24
Q

Normal distribution curve

A

All measures of central tendency fall around the centre of the curve as most people achieved this: the median nor mode was not skewed to be higher/lower because there were no outlier scores

25
Q

Normal distribution curves usually represent the…

A

Average sample of the whole population

26
Q

Negatively skewed distribution curve

A

The mean is smaller than the mode (mode is the peak) (mean is to the left of the mode)
Curve slopes into the y axis

27
Q

What do negatively skewed distribution curves show?

A

More people scored towards the higher end of data set and achieved a high score (mode is high)
But data and mean is skewed by few people who scored lower (negative skew)

28
Q

How to remember negatively skewed distribution?

A

Slide that hits into the y axis (slopes into y axis and steep climb as the ladder on the right side)
A NEGATIVE EXPERIENCE

29
Q

Positively skewed distribution curve

A

The mean is larger than the mode (mode is peak) mode is further to the right than the mode peak
Curve slopes away from the y axis

30
Q

What do positively skewed distribution curves show?

A

More people achieved a lower score thus mode decreases but few people scored very high thus giving a positive skew
So data and mean is skewed by those who achieved toward higher end thus positive skew

31
Q

How to remember positively skewed distribution?

A

Slide that you climb the steep end near the y axis and slide away from it
A POSITIVE EXPIRIENCE

32
Q

When can we use standard deviation on a distribution curve?

A

Only for normal distribution curves not one with positive or negative skew

33
Q

Standard deviation on a distribution curve: 1 s.d

A

34% of results will score 1 s.d above the mean
34% of results will score 1 s.d below the mean
68% of results will score 1 s.d above and below the mean

34
Q

Standard deviation on a distribution curve: 2 s.d

A

95% will score 2 s.d above and below the mean

A level psychology (53 decks)

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