Statistics 101
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Transcript Statistics 101
Statistics 101
Chapter 10
Section 2
How to run a significance test
Step 1: Identify the population of interest and the
parameter you want to draw conclusions about.
State the null and alternative hypothesis in words
and symbols.
Step 2: Choose the appropriate inference
procedure. Verify the conditions for using the
selected process.
Step 3: Carry out the inference procedure. Calculate
the test statistic and find the P-value.
Step 4: Interpret your results in the context of the
problem.
Tests of significance
Confidence intervals – estimate a population
parameter
Tests of significance: assess the evidence
provided by data about some claim
concerning a population
An outcome that would rarely happen if a
claim were true is good evidence that the
claim is not true.
Reasoning of tests of
significance
Null hypothesis: there is no effect or change
in the population H0 (H-nought)
Sweetness of colas:
H0:μ = 0
Alternative Hypothesis: Ha is that the cola does lose
sweetness.
Ha: μ > 0
P - value
Probability of a result at least as far out as
the result we actually got.
Small P-values are evidence against H0
because they say that the observed result is
unlikely to occur just by chance.
How small is small enough to persuade us?
0.05 is statistically significant.
Stating Hypotheses
Null hypothesis.
Alternative hypothesis
H0: μ = 0
Ha: μ > 0
This is called one-sided because we are
interested only in deviations from the null
hypothesis in one direction.
Two-sided
Job Diagnosis Survey p 565
H0: μ = 0
Ha: μ = 0
Statistical Significance
If the P-value is as small or smaller than
alpha, we say that the data are statistically
significant at level alpha
Test for population mean
Identify the population of interest and the
parameter
State the null and alternative hypothesis in
words and symbols
Choose the appropriate inference procedure
Calculate the test statistic
Find the P-value
Interpret your results
Z test for a population mean
To test H0: μ = μ0 based on an SRS of size n
with unknown μ and known standard
deviation σ, compute one-sample z statistic
Z = (x - μ0 ) / σ / √n
Tests with fixed significance
level
Fail to reject instead of accept implies a
100% certainty in H0
Since 0.06 > 0.05 we fail to reject the H0.
There is not significance to conclude that the
students are less skilled.
This is example 10.15
Exercises
10.27, 10.29 – 10.32, 10.33, 10.38, 10.40,
10.41, 10.45, 10.49, 10.56