Question

Discuss why one would use inferential statistics rather than correlational statistics. Be sure to clearly identify these reasons and back your statements with examples

Answer 1

Answer

Beacause Inferential statistics that to make judgement of probability that observed difference between the is dependable one or one that might happened by the chance in this study.

Thus interfere with statistics to make interference from our data to more general conditions.

example, if we met a group of people men and women and the women earned more than the men, we could infer that women, generally, earned more than men. Here inferential statistics allows us to do is make that inference or not with some degree of certainty that what we are inferring from the sample applies to a wider group of men and women, i.e. the population of men and women .but in Correlational statistics is used to test relationships between quantitative variables or categorical variables. In other words, it’s a measure of how things are related. The study of how variables are correlated is called correlation analysis.

An example of positive correlation would be height and weight. Taller people tend to be heavier.

An example of negative correlation would be height above sea level and temperature. As you climb the mountain (increase in height) it gets colder (decrease in temperature).

By discussing above statement with example ,can conclude one would use inferential statistics rather than coorelational statistics because inferential statistics is more effective and accurate,it can also helps to draw clear cut picture of data analysis.