Measures of central tendency Flashcards

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1
Q

Mean
Strengths?
Weaknesses?

A

Strengths
Takes into account all the scores in the data set meaning that it is representative

Weaknesses
Can be skewed by extreme data = unrepresentative of raw data set

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2
Q

Mode
Strengths? What is it not effected by? why?
Data does not have to be?
Weaknesses?- what question is raised? why?

A

Strengths
As the mode only focuses on the most frequent score, it is not effected by extreme scores
Data can be non numerical

Weaknesses
It ignores the other scores as it is only interested in the most frequent score, so is it an accurate measure of central tendency if all of the scores are not considered?

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3
Q

Median

A

Strength

Less likely to be skewd as it is only interested in the middle number

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3
Q

Median
strength?
Weaknesses?

A

Strength
Less likely to be skewed as it is only interested in the middle number

Weakness
If the data set is large, it is time consuming to put all the scores into order
As only the middle number is looked at, is the medium really an accurate measure for central tendency?

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4
Q

Range
Strength?
Weaknesses? What does it not indicate? why?

A

strength
Easy to calculate

Weakness
can be skewed by outliers
Does not indicate the distribution of the scores as it only looks at the highest and lowest scores

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5
Q

Variance
what does it indicate?
What does a smaller variance mean?

A

Indicates how spread apart the data is from each of the conditon from the mean score

Smaller variance = less spread out

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5
Q

Variance
what does it indicate?
What does a smaller variance mean?

A

Indicates how spread apart the data is from each of the conditon from the mean score

Smaller variance = less spread out

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6
Q

Variance

A

1- mean score each condition
2- subtract mean score from their score, can be + or -
3- Sqaure ‘d’ score = d2
4- Add all the d2 scores to get the sum of differences squared
5- calculate the mean by dividing by n-1
n = number of participants

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7
Q

What are the different ways of displaying data?

A
Line graph = data overtime
scatter graph = correlation
bar chart = bars not touching- categories
pie chart = proportion of a total
histogram = continuous data
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