Chapter 4: Making Inferences - Confidence Limits and Statistical Significance

Standard Error

the name given to the standard deviation of the sampling distribution

Probability

always goes from 0 to 1

Probability

is counter-intuitive

Probability

it is counter-intuitive because we like to believe that we know things rather than making probability statements about them

Null Hypothesis

symbolized by Hₒ.

Null Hypothesis

logical counterpart of the alternative hypothesis

Null Hypothesis

it either specifies that there is no effect, or that there is real effect in the direction opposite to that specified by the alternative hypothesis

Alternative Hypothesis

symbolized by H₁.

Alternative Hypothesis

the hypothesis that claims the differences in results between the conditions is due to the independent variable

One-tailed (or directional) hypothesis

if we are looking for a result in one direction only

Two-tailed (or non-directional) hypothesis

if we are looking for a result in either direection

a-value or level of significance

value or cut-off we use before we decide to reject the null hypothesis

probability value (p-value)

probability of a result occurring if the null hypothesis is true, not the probability that the null hypothesis is true

0.05 (1 in 20 or 5%)

somewhat arbitrary, but is the convention that is used throughout much of science

Statistically significant

when the probability is found to be below 0.05 (or whatever cut-off we are using)

Statistical Significance

determining how likely it is that the result could have occurred by chance

Statistical Significance

the probability that the pattern of data that was observed did not occur by chance

Alpha level

indicates that the probability that the observed finding occurred by chance is less than 5 in 100

statistically significant result

does not necessarily have to be "meaning", and is not necessarily "important", it just means that there is a less than 1 in 20 probability that the results would have occurred if the null hypothesis were correct

Type I Error

when we reject the null hypothesis because there is only a low probability of the result occurring if it is true, but it might actually be true after all

Type II Error

the other logical error when we fail to reject the null hypothesis when it is not true

Confidence Intervals

the range of values which are the likely range of the population value

Confidence Limits

the largest and the smallest values in the interval

Degrees of Freedom or df

the number of scores that are free to vary in calculating a statistic