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Inferential Statistics

INFERENTIAL STATISTICS
Inferential statistics may simply be defined as the process of drawing conclusion about a population on the basis of information contained in a sample taken from the population. Moreover, it is the process of selecting and using a sample statistic to draw inferences about a population parameter. Inferential statistical are mainly used when we have access to a sample drawn from a population and also when we all the raw scores that could theoretically exist in the total population are not absent.

STRATEGIES
Statistics inference mainly uses two strategies, namely estimation and hypothesis testing.

I) ESTIMATION
This is mainly used to make inferences about characteristics of populations from information contained in samples. Two types of estimates can be made about a population that is point estimate and interval estimate.

Point estimate
A point estimate is a single number that is used to estimate an unknown population parameter. For example, if while watching members of a football team come onto the field, you say “I bet their line must weigh 250pounds.” You’ve made a point estimate. A department chairwoman would make a point estimate if she said, “Our current data indicate that this course will have 350 students in the fall.

A point estimate is often insufficient because it is either right or wrong. If you are told only that the chairwoman’s point estimate of enrollment is wrong, you do not know how wrong it is, and you cannot be certain of the estimate reliability. If you learnt that that is off by only ten students, you would accept 350 students as good estimate of future enrollment. But if the estimate is off by 90 students, you would reject it much more useful if it is accompanied by an estimate of the error that might be involved.

Interval Estimate
An interval estimate is a range of values to estimate a population parameter. It indicates the error in...