inferential statistics Flashcards by Jodie Hancock

using something that can be observed (from a sample) to make an inference about something that cannot be observed (an entire population)

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when we analyse our data we assume there is/is no difference between our experimental groups.

is no difference

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how do we calulate the probability

calculate probability of observing differences in sample if there is no difference between populations

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As the t-value gets bigger, the probability gets..

smaller

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If it’s less likely that the null hypothesis is correct, is it more or less likely that the results are due to actual differences between our two experimental groups?

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is the t value is the largest what does that mean about the null hypothesis

the null hypothesis is least likely to be correct

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As the t-value gets bigger, the probability of observing our results if the null hypothesis is correct gets…

smaller

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the t value helps us find the probability of….. our results, if the null hypothesis is ……..

the t value helps us find the probability of OBSERVING our results, if the null hypothesis is CORRECT

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The smaller the t-value, the bigger the probability of the null hypothesis being…

incorrect

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the t value gets ….. as the probability of observing our results gets …..

the t value gets BIGGER as the probability of observing our results gets SMALLER

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steps for sign test

work out type of hypothesis
work out the signs for each number
add up all the pluses and the minuses, discards =
the lowest of the + and - is the S value
N is total minus the equals
find critical value for 0.05
significiance statement

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how to word a significance statement for the sign test

the s value is…… and which higher/lower/equal to the critical value of ….. wmt the difference is not/is significant

lower/equal is significant
higher is not significant

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what could be a reason that data is ordinal and not interval

you cannot assume the data is ordinal because eg verbal errors cannot be assumed of equal size

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what does p<0.05 mean

probability is less than 95% suggesting the results are not due to chance

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what are the 3 factors that affect the t value

difference between means
dispersion of the data
size of samples

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how can the difference between means affect the t value

The bigger the difference between the means of two samples, the bigger the t-value

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As the difference between the means get bigger, the probability of observing our results if the null hypothesis is correct gets…

smaller

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the bigger the difference between the means, the …. the probability of observing our results if the null hypothesis is correct.

smaller

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As the dispersion of the samples’ distributions gets bigger, the t-value gets…

smaller

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The bigger the dispersion, the … the probability of observing our results if the null hypothesis is correct, and so the …. likely it is that the null hypothesis is correct.

bigger, more likely

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The bigger the dispersion, the …… the t-value.

smller

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The bigger the dispersion, the …. likely it is that our null hypothesis is correct.

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The smaller the t-value, the …. likely it is that our null hypothesis is correct.

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The smaller the dispersion, the bigger the probability of observing our results if the null hypothesis is incorrect. true or false

true

The smaller the t-value, the more likely it is that our null hypothesis is correct. true or false

true

The bigger the dispersion, the less likely it is that our null hypothesis is correct. true or false

false

As the sample size increases, the t-value gets..

biggger

As the sample size gets bigger, the probability of observing our results if the null hypothesis is correct gets…

smaller so the less likely null is correct

As the sample size decreases, it becomes ..... likely our null hypothesis is correct.

probabilities are always expressed as either…

fractions percentages a number between 0 and 1

If a t-value gives a probability of 0.03 this means there is a .... probability of obersving our results if the null H is ....

3% correct

If a t-value gives a probability of 12% this means that there is a .... probability of observing our results if the null H is ....

12% correct

what is p value

probability of observing our results if the null hypothesis correct

what does a p=56% mean

if the null hypothesis is correct, there is a 56% probability of observing our results

a bigger t value gives a .... p value

smaller

As the p-value gets smaller, is the null hypothesis more or less likely to be correct?

less

Grace and Ruby carry out separate experiments. Grace gets a p-value of 17% and Ruby gets a p-value of 13%. Who is more likely to reject the null hypothesis?

ruby

As the p-value gets bigger, there is a bigger probability of observing our results if the null hypothesis is correct. True or False?

true

James and Sophie carry out separate experiments. James gets a p-value of $0.04$ and Sophie gets a probability of $4\%$. Who is more likely to reject their null hypothesis?

equally likely

what do we use a t test for

to decide whether to accept or reject our null hypothesis

how do we know what size of p value will mean accept or reject thenull H

the experimenter decides at the begining of the study, they create a significance level

If a researcher decides on a significance level of 5% for their experiment, then they will decide that their null hypothesis is incorrect if they obtain a p value of

5% or less

What is the name of the value at which a researcher switches from accepting the null hypothesis, to rejecting it?

significance level

If the p-value a researcher obtains is smaller than or equal to the significance level that they selected, then they…

reject the null H

If Jack sets his significance level at 20 % and then obtains a p-value of 19.9% in his study, can he reject the null hypothesis?

Yes, because his p-value is below the significance level.

A type 1 error is when researchers…

incorrectly reject the null hypothesis, and say there is a real difference between two experimental groups when there isn’t one.

if a researcher chooses a significance level of 15% what is the proability of making a type 1 error

15%

what does the significance level tell us

how likely we are to make a type 1 error

as the significance level gets smaller is it more or less likely that type 1 errors will occur

less likely

if researchers dont want to cause any type 1 errors what might they do

set the significance level really low

if a the significance level is low what is less likely to happen in regards to the null H and type 2 error

it is less likely itll be rejected and increases possibility of a type 2 error

what is a type 2 error

failure to reject the null hypothesis when there actually was a difference between experimental groups fail to reject the null hypothesis, and say there isn’t a difference between the two experimental groups and conclude their results happened by chance when there actually is a difference

To balance the risk of a Type 1 and Type 2 error, what value do we usually set the significance level at?

setting SL at 5% means what in terms of nullH

we reject the null hypothesis is theres less than 5% probability of it being correct

Petra is investigating the effectiveness of reading on patients with anxiety. She selects a significance level of 5% and obtains a p-value of 0.05. She rejects the null hypothesis typ1, 2 or no error

none

. Osman is investigating the effectiveness of consistent sleeping patterns on patients with depression. He selects a significance level of 0.06% and obtains a p-value of 0.06. He fails to reject the null hypothesis, even though consistent sleep patterns were actually effective for many patients. 1,2 or no error

Kate is investigating the effectiveness of exercise on memory recall. She selects a significance level of 10% and obtains a p-value of 8%. She rejects the null hypothesis, even though exercise didn’t actually improve memory recall. 1, 2, no error

Hanna is investigating the effect of pets on happiness levels for people with depression. She sets the significance level at $0.11\%$, but accepts her null hypothesis. Which error is most likely to have occurred?

If a researcher sets their significance level at 5% and gets a p-value of 14% should they reject the null hypothesis?

What is the name of the probability of observing our results if the null hypothesis is correct?

p value

Jack sets his significance level at 5% and obtains a t-value (t=2.178). The critical t-value for his significance level is t=2.086. Can Jack reject the null hypothesis?

Yes, because his obtained t-value is bigger than the critical t-value.

We reject the null hypothesis if the obtained t-value is…

bigger than, or equal to, the critical t-value for our significance level.

as the sample size increases what happens to the t value

it increases

For the unrelated t-test, what is the degrees of freedom?

The total sample size across the two groups subtract 2

For the related t-test, what is the degrees of freedom?

For a related t-test, the degrees of freedom is the sample size subtract 1

when is an alternative hypothesis needed

when we reject the null hypothesis

if the null hypothesis was: no different between heights of first borns and second borns. and it was rejected, what would the alternative hypothesis be

first borns are taller than second borns

the alternative hypothesis is the hypothesis that is our results are .....

unlikely to have happened by chance and there is a real difference between the experimental groups is the opposite of the null hypothesis.

which is one tailed, which is two tailed

directional is one tailed non directional is two tailed