Reference no: EM133017201
A statistical hypothesis is an assumption about a population parameter. This assumption may or may not be true. Hypothesis testing refers to the formal procedures used by statisticians to accept or reject statistical hypotheses.
The best way to determine whether a statistical hypothesis is true would be to examine the entire population. Since that is often impractical, researchers typically examine a random sample from the population. If sample data are not consistent with the statistical hypothesis, the hypothesis is rejected.
There are two types of statistical hypotheses.
Null hypothesis. The null hypothesis is usually the hypothesis that sample observations result purely from chance.
Alternative hypothesis. The alternative hypothesis is the hypothesis that sample observations are influenced by some non- random cause.
For example, suppose we wanted to determine whether a coin was fair and balanced. A null hypothesis might be that half the flips would result in Heads and half, in Tails. The alternative hypothesis might be that the number of Heads and Tails would be very different.
References: Copper, D. R., & Schindler, P. (2014). Business research methods (12th ed.)
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