# why do you think hypothesis testing is important in statistics?

Question Description

For this week’s discussion, why do you think hypothesis testing
comments to the concept of null and alternative hypotheses and describe
what these mean. Your initial response to the Discussion topic should be
a minimum of 200 words. You should also provide at least two responses
to your classmates that should be a minimum of 100 words. In your peer
replies, you are encouraged to challenge responses to promote critical
thinking on all sides of a discussion.

Classmate Post #1

Hypothesis
testing is the process of using statistics to determine the probability
that a specific hypothesis is true. It’s an essential procedure in
statistics. A hypothesis test evaluates two mutually exclusive
statements about a population to determine which statement is best
supported by the sample data. A hypothesis predicts the relationship
between two variables. Hypothesis testing is common in statistics as a
method of making decisions using data. In other words, testing a
hypothesis is trying to determine if your observation of some phenomenon
is likely to have really occurred based on statistics. This test
normally comes from a statistical standpoint. The null hypothesis always
states that the population parameter is equal to the claimed value. The
alternative hypothesis should be decided upon before collecting or
looking at any data, so as not to influence the results.

Reference:

Classmate Post #2

Hello,

Hypothesis testing is important in statistics because it helps to draw
conclusions and make decisions about the nature of populations. It is
proof that your data is significant and didn’t occur by chance. A
conclusion is determined by examining a sample of a population. A
decision is made based on the tests between two hypotheses. Two
determines which statement supports the data. The hypothesis or
conclusion about the population can have two outcomes. On one end you
have a null hypothesis and then the alternative hypothesis.

When
testing a hypothesis you form your opinion on what you think is
occurring in the population to validate that one group is different from
the other. Your conclusion can either be a null hypothesis or an
alternative hypothesis. A null hypothesis states that nothing happened
or there wasn’t any differences noted or no cause and effect. The
alternative hypothesis, which states that something happened and there
are differences. With hypothesis testing, you are trying to prove that
there was a change and you are trying to disprove the null hypothesis.

Reference: