phase 5 project

Running head: HYPOTHESIS TEST 0

Project Phase 3 – Scenario 2

Author Note

This paper is being submitted on

Explain the 8 Steps in hypothesis testing.

1. State null hypothesis- this is the opposite of the expected results, the importance of stating the null hypothesis is because according to Karl Popper’s principle or Falsifiabilty, it not possible to exclusively confirm a hypothesis but it is possible to conclusively negate a hypothesis.

2. Alternative hypothesis- this is indication of what the experiment expects. It is stated as not all equal, because despite the fact that it is possible to have not all equal variables it is only one of the many chances. For instance, when comparing effect of infectious disease of the colour of urine the alternative hypothesis can state that disease 1 results in tinting of the colour of urine to yellow but disease 2, 3… and normal un-infected persons do not differ in the colour of urine.

3. Set α- this is the level of significance. This is the probability or chance of committing the ‘grievous’ error type one denoted by α

There are two types of errors;

4. Data collection- it’s important to use valid data collection techniques possibly for this case use observational or experimental methods

5. Stating and calculating the statistics for the study- this are the statistic values tested which include the mean, population, sample proportion and the difference in mean and sample proportions.

6. Decide on the test to be used- there are basically two types of tests; one tailed and two tailed. The decision is reached depending on the spread of error; two tailed is used when error spread is on two extremes side while one tailed test is used when error is spread on one side in the distribution.

7. Create accept and reject regions- a critical F value is established, you can establish the study F value from the statistical tables it is also called the Fα. It represent the minimum value for the study test statistics which determine which values should be rejected. With the value of F you locate it in the F distribution which form the location for boundary for acceptance and rejection.

8. Standardize the test statistics to draw a conclusion- using step 5 and 6 you can make some inference on the study, but to make more specific conclusion computation of z-test will help decide on the whether to reject or accept the hypothesis. In such cases p-value lower then α, then null hypothesis H0 is conclusively negated and therefore should accept the alternative hypothesis HA.

In testing a hypothesis using the above eight steps I prefer using critical value.

This method include the coming up with the unlikely or likely which involves testing is the involved test statistics are more extreme than it would be possible if the null hypothesis was to true. It’s a straightforward, if the critical value if greater than the critical value α and therefore, the null hypothesis is incorrect which means the alternative hypothesis is accepted. It is has more valid explanation for accepting or rejecting a null hypothesis using this method.

Performing the hypothesis.

Claim:

The average age of patients admitted to NLEX hospital is less than 65 years is the test claim using α=0.05 in a normally distributed population of unknown standard deviation

Mean= 65 years

Scenario 2

Mean= 62.82 years scenario 1 standard deviation= 8.3 with a sample size of 60.

1. The H0 will be that the average age of patients admitted to NLEX hospital is 65 years.

2. The HA is the average age of patients admitted to NLEX hospital is less than $ 65,000

3. Therefore t=(65-62.82)(8.3/√60)= 2.336

4. α=0.05 and n-1 degree of freedom which is 60-1=59 in one tiled test.

5. Tabulated t-value is 1.65.

6. With a greater computed t-value of 2.336 against tableted t-value of 1.65 the null hypothesis is conclusively negated.

Based on the option selected;

1. Write the alternative and null hypothesis and indicate which the claim is.

H0 =µ=65 years

HA= µ˂ 65 years

The alternative hypothesis is the claim hypothesis.

1. Is the test two tailed, left tailed or right tailed? Explain.

It’s left tailed, because a test to find probability/chance of the null hypothesis and the mean is on the left side of the normal distribution curve.

1. Which test will you use to test the hypothesis test, z-test or t-test? Explain.

T-test. Because the data is normally distributed in the population of unknown standard deviation.

1. What is the value of the test statistic? Show your calculations.

T= 2.336

T= (65-62.82) (8.3/√60)

T= 2.18/1.072

=2.336

1. What is the p-value? Explain how you determine it.

The value of p=0.05

Determined by finding if Z is beyond the statistic test; looking up in the z-table for the probability that it is greater than alternative hypothesis and subtract from 1.

1. What is the critical value and how to calculate it?

T (0.5-0.05) d= 0.45

T-value=1.65

Subtracting alpha (0.05) from 0.5=0.45 (in the z-table that is 0.455) the looking up in the z-table for the corresponding value is 1.65.

1. Decision, whether to reject of accept the null hypothesis.

I reject the null hypothesis, because the computed t-value 2.336 is greater than tabulated t-value of 1.65.

1. State the conclusion.

I reject the null hypothesis because it has been conclusively been negated i.e. the average patients admitted in NLEX hospital is less than 65 years.

Reference

Lane, D. M. (2002). Steps in Hypothesis Testing.