Question

Some definitions or T/F concerning probability distributions covered, confidence intervals, and hypothesis testing

Answer 1

Solution:

Given that,

Confidence intervals:

A confidence interval is an estimate of an interval in statistics that may contain a population parameter. The unknown population

parameter is found through a sample parameter calculated from the sampled data. For example, the population mean μ is found

using the sample mean x̅.

The interval is generally defined by its lower and upper bounds. The confidence interval is expressed as a percentage (the

most frequently quoted percentages are 90%, 95%, and 99%). The percentage is called the confidence level.

Hypothesis testing:

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.

There are two types of statistical hypotheses.

1. The null hypothesis, denoted by Ho, is usually the hypothesis that sample observations result purely from chance.

2. The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some non-

random cause.