Chapter 13 – Understand Research Results: Statistical Inference

Infer whether the results that were obtained in a particular study would still

occur if the study were repeated over and over again

SAMPLES AND POPULATIONS

Researchers conduct studies from a single sample of research participants

They rarely conduct studies from entire populations; their findings are based

ons ample data

So with this sample data, you want to be able to make statements about the

entire populations and so, you want ot know if the results will be the same if

the experiment were conducted again with a new sample

Inferential statistics: used to determine whether we can, in fact, make

statements that the results reflect what would happen if we were to conduct

the experiment again and again with multiple samples

Asking if whether we can infer that the difference in the sample means

reflects a true difference in the population means

Inferential statistics allow us to arrive at such conclusions on the basis of

sample data

INFERENTIAL STATISTICS

Importance of ensuring that the groups are equivalent in every way except

the independent variable manipulation

Equivalence of groups are maintained by controlling all other variables or by

randomization

If the groups are equivalent, then you assume that any differences found in

the dependent variable are due to the effect of the independent variable

Differences between any two groups will amost never be zero

oThis means that there will be some difference in the sample means,

even if you manage to carry out the experiment properly

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oThis happens because you are dealing with samples and not

populations

oRandom or chance error will be responsible for some difference in the

means even if the independent variable had no effect on the dependent

variable

oPoint is, the difference in the sample means reflects any true difference

in the population means plus any random error

Inferential statistics allow researchers to make inferences about that true

difference in the population on the basis of the sample data

Inferential statistics give the probability that the difference between means

reflects random error rather than a real difference

NULL AND RESEARCH HYPOTHESES

Statistical inference begins with a statement of the null hypothesis and a

research (or alternative) hypothesis

Null hypothesis: the population means are equal – the observied difference

is due to random error

oStates that the independent variable had no effect

Research hypothesis: the populations means are, in fact, not equal

oStates that the independent variable did have an effect

If we can determine that the null hypothesis is incorrect, then we accept the

research hypothesis as correct

Acceptance of the research hypothesis means that the independent variable

had an effect on the dependent variable

With the null hypothesis, we know precisely the probability of the outcome of

the study occurring if the null hypothesis is correct

So we want to infer that the research hypothesis is correct only by rejective

the null hypothesis

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The null hypothesis is rejected when there is a very low probability that the

obtained results could be due to random error

Statistical significance: a significant result is one that has a very low

probability of occurring if the population means are equal

Significance indicates that there is a low probability that the difference

between the obtained sample means was due to random error

Significance is a matter of probability

PROBABILITY AND SAMPLING DISTRIBUTIONS

Probability: the likelihood of the occurrence of some event or outcome

We want to specify the probability that an event (difference between means in

the sample) will occur if there is no difference in the population

If the probability is very low, then we reject the possibility that only random

or chance error is responsible for the obtained difference in means

Probability: The Case of ESP

Your friend claims to have ESP (extrasensory perception) ability

You test your friend with a set of five cards that are used in ESP research – a

different symbol is on each card

You look at each card and think about the symbol and yoru friend tells you

which symbol you are thinking about

In the experiment you have 10 trials – each of the five cards is shown two

times in a random order

You must know whether your friend’s answers are random error (guessing) or

if they are more than random error

The null hypothesis is that only random error is occurring, so they are only

guessing

The research hypothesis is that the number of correct answers shows more

than the guessing

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## Document Summary

Chapter 13 understand research results: statistical inference. Infer whether the results that were obtained in a particular study would still occur if the study were repeated over and over again. researchers conduct studies from a single sample of research participants. they rarely conduct studies from entire populations; their findings are based ons ample data. Inferential statistics: used to determine whether we can, in fact, make statements that the results reflect what would happen if we were to conduct the experiment again and again with multiple samples. asking if whether we can infer that the difference in the sample means reflects a true difference in the population means. Inferential statistics allow us to arrive at such conclusions on the basis of sample data. Importance of ensuring that the groups are equivalent in every way except the independent variable manipulation. equivalence of groups are maintained by controlling all other variables or by randomization.