Читать книгу Methods in Psychological Research - Annabel Ness Evans - Страница 83

Inferential statistics are used to generalize the findings of a study to a whole population. An inference is a general statement based on limited data. Statistics are used to attach a probability estimate to that statement. For example, a typical weather forecast does not tell you that it will rain tomorrow afternoon. Instead, the report will indicate the probability of rain tomorrow. Indeed, the forecast here for tomorrow is a 60% chance of rain. The problem with making an inference is that we might be wrong. No one can predict the future, but based on good meteorological information, an expert is able to estimate the probability of rain tomorrow. Similarly, in research, we cannot make generalized statements about everyone when we only include a sample of the population in our study. Instead, we attach a probability estimate to our statements.

When you read the results of research articles, the two most common uses of inferential statistics will be hypothesis testing and confidence interval estimation.

 Does wearing earplugs improve test performance?

 Is exercise an effective treatment for depression?

 Is there a relationship between hours of sleep and ability to concentrate?

 Are married couples happier than single individuals?

These are all examples of research hypotheses that could be tested using inferential tests of significance. What about the following?

 Does the general public have confidence in its nation’s leader?

 How many hours of sleep do most adults get?

 At what age do most people begin dating?

These are all examples of research with a focus on describing attitudes and/or behavior of a population. This type of research, which is more common in sociology than in psychology, uses confidence interval estimation instead of tests of significance.

The vast majority of psychological research involves testing a research hypothesis. So let’s first look at the types of tests of significance you will likely see in the literature and then look at confidence intervals.