Question

A smaller p value gives us stronger evidence against the null hypothesis.

TRUE or FALSE and explain briefly

The p value is the probability that the null hypothesis is true.

TRUE or FALSE and explain briefly

Answer #1

**A smaller p value gives us stronger evidence against the
null hypothesis.**

**TRUE**

(because we reject the null hypothesis if p value is less than level of segnificance ,so as p value will be small it will give stronger evidence against H0.

**The p value is the probability that the null hypothesis
is true.**

**FALSE**

(because p value is the probability that the test statistic is as extreme or more extreme than is actually observed, assuming the null hypothesis is true)

Consider the following statements.
(i) The smaller the p-value, the stronger the evidence
is in favor of the null hypothesis.
(ii) The p-value forms the borderline between values
of the test statistic that would result in rejecting the null
hypothesis and values of the test statistic that would result in
not rejecting the null hypothesis.
(iii) The p-value is calculated under the assumption
that the null hypothesis is true.
Determine which of the above statements are true (1) or false...

T/F
(4) If a sample gives strong enough evidence to reject the null
at the 5% level, it will also give strong enough evince to reject
the null at the 1% level.
(5) A smaller p value gives us stronger evidence against the
null hypothesis.

True or False: The higher the level of significance of a
hypothesis test, the stronger the evidence we require to reject the
null hypothesis.
True or False: The purpose of a hypothesis test is to assess the
evidence in favour of the null hypothesis.
True or False: The higher the p-value of a hypothesis test, the
more evidence we have to reject the null hypothesis.

True or False: The higher the level of significance of a
hypothesis test, the stronger the evidence we require to reject the
null hypothesis.
True or False: The purpose of a hypothesis test is to assess the
evidence in favour of the null hypothesis.
True or False: The higher the p-value of a hypothesis test, the
more evidence we have to reject the null hypothesis.

1) The larger the chi-square statistic, the weaker the evidence
against the null hypothesis. True or False
2) The more similar the conditional distributions in a two-way
table are, the larger the P-value of the chi-square test
becomes. True or False

1. The P-value of a test of the null hypothesis is
a. the probability the null hypothesis is true.
b. the probability the null hypothesis is false.
c. the probability, assuming the null hypothesis is false, that
the test statistic will take a value at least as extreme as that
actually observed.
d. the probability, assuming the null hypothesis is true, that
the test statistic will take a value at least as extreme as that
actually observed.
2. The P-value...

Assuming that the null hypothesis is true, a p-value is
the probability of observing a sample value as extreme as, or more
extreme than, the observed sample observation.
True or False

true or false? At the end of a hypothesis test, if P≥α
then the null hypothesis is accepted.

The P-value for a hypothesis test is given. Determine whether
the strength of the evidence against the null hypothesis is
weak/none, moderate, strong, or very strong. P = 0.31
A) Strong B) Very strong C) Weak or none D) Moderate

True or False: For all hypothesis tests, a small p-value means
we will reject the null.
True or False: If you are testing the means of two groups, then
you would use ANOVA.
True or False: A two-sample confidence interval must capture
zero to show the groups are different.
True or False: The test statistic for ANOVA is the
f-statistic.
True or False: For Chi-Square tests, if the observed counts and
expected counts are extremely different, then we would have...

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