Statistics Flashcards

(28 cards)

1
Q

Position of mean median and mode in the normal distribution

A

The mean median and mode are the SAME in a normal distribution

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2
Q

Effect of the symmetricality of the normal distribution

A

50% of the population lie above the mean and 50% lie below the mean

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3
Q

What is the range of a set of data

A

Range = largest value – smallest value

The range tells us what the total spread of the data is.

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4
Q

Problems with using the range to look at the spread of a data set

A

The range uses the highest and lowest data points which may be extreme (outliers) therefore giving a false impression of how spread the data really is.

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5
Q

Define standard deviation and what it measures

A

A measure of the spread of the data

This is a measure of the spread of data on either side of the mean. It is a measure of variability.

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6
Q

is standard deviation as affected by outliers as the range

A

Standard deviation (SD) uses all the data and is less affected by outliers.

However The standard deviation is only meaningful provided there are sufficient data points (usually a minimum of 5).

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7
Q

What is the purpose of a statistical test

A

To determine the probability that your results could have occurred by chance.

(and not due to a biological causal mechanism)

A statistical test enables us to calculate the probability that our results are real or due to chance.

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8
Q

How statistically certain must you be of your results

A

It is generally accepted that we want to be at least 95% certain that our results are real (or 5% certain that our observed results were due to chance).

This can be expressed as a probability (p = 0.05).

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9
Q

What is spearman’s rank correlation coefficient

A

Spearman’s Rank Correlation is a statistical test to test whether there is a significant relationship between two sets of data.

The Spearman’s Rank Correlation test can only be used if there are at least 10 (ideally at least 15) pairs of data.

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10
Q

Define correlation

A

Where a change in one variable is associated with a change in another variable.

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11
Q

What does a strong spearman’s rank indicate

A

Causation implies that one variable causes the other variable to happen i.e. there is an underlying causal mechanism.

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12
Q

Interpreting the values for spearman’s correlation coefficient

A

rs will be a number between – 1 and +1

A negative value for rs implies a negative correlation

A positive value for rs implies a positive correlation

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13
Q

What are degrees of freedom

A

the number of values in a data set that are free to vary.

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14
Q

How to calculate the degrees of freedom

A

Degrees of freedom = n - 2

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15
Q

What does a p value of 0.05 mean

spearmans

A

p = 0.05 means that there is a 5% probability that our correlation is due to chance alone.

Alternatively we can say that there is a 95% probability that any correlation is not due to chance i.e. there is an established biological causal factor or mechanism.

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16
Q

What does a T test do

A

Compares means

17
Q

What does a T test require

A

Data that a mean can be calculated from

18
Q

What does a T test measure

A

The significance of the difference between observed data and expected results when data fits into categories

Compares the means of set sets of data

19
Q

Unpaired vs paired T test

A

Paired t test compares data from the same group before and after a change

Unpaired T test tests two separate/ independent sets of data

20
Q

How to make a study more valid

A

increase sample size

Use similar group sizes

Ensure similar starting conditions- e.g. health conditions or gender

21
Q

T test assumptions

A

Continuous variables

Variables are normally distributed

Roughly equal sample sizes

Each group has had unbiased samples taken

22
Q

How to calculate degrees of freedom for T test

A

(n1 - 1) + (n2 -1)

23
Q

What does a t value that this larger than the critical value mean for a conclusion

A

reject null hypothesis

95% certainty that there is a significant difference between the two means with an underlying causal relationship

24
Q

What is chi squared used for

A

Used to compare observed results with expected results.

The data must be categoric e.g. number of red flowers, white flowers

25
Chi squared null hypothesis
A null hypothesis starts on the basis that there is no significant difference between observed and expected results
26
Chi squared degrees of freedom
number of categories - 1
27
Conclusion to draw from a value of chi squared being greater than the critical value
Large values of X2 suggest that the difference between the observed and expected values is statistically significant. The probability that the difference is due to chance is very low.
28
Conclusions from the value of chi squared is less than the critical value
there is NO significant difference between the observed and expected results. Any difference is due to chance alone. (Accept null hypothesis)