Question

Q1) Why we sometimes get unexpected results during hypothesis testing? Q2) What is the relationship between level of significance and confidence level? Q3) State the different factors on which sample size depends? Q4) What is the difference between 2 and t test? (5) Draw distribution curve and write hypothesis for the left one tail and right one tail.

Answer 1

1. The one‐tailed testing is that you are testing a more extensive null hypothesis and so your ability to detect unexpected results (make inferences on the underlying biology) can be restricted when the null hypothesis is not rejected.

2. The confidence level is equivalent to 1 – the alpha level. So, if your significance level is 0.05, the corresponding confidence level is 95%. If the P-value is less than your significance (alpha) level, the hypothesis test is statistically significant.

3. The factors affecting sample sizes are study design, method of sampling, and outcome measures – effect size, standard deviation, study power, and significance level.

4. Generally, z-tests are used when we have large sample sizes (n > 30), whereas t-tests are most helpful with a smaller sample size (n < 30). Both methods assume a normal distribution of the data, but the z-tests are most useful when the standard deviation is known.

5. Right tail:

The curve is:

Distribution Plot Normal, Mean=0, StDev=1 0.4 0.3 Density 0.2 0.1 0.05 0.0 1.645 0 X

The hypothesis being tested is:

H₀: µ =

H_a: µ >

Left tail:

The curve is:

The hypothesis being tested is:

H₀: µ =

H_a: µ <

Thank you! :)