Hypothesis Testing

 HYPOTHESIS TESTING TASK FOR INDIVIDUAL BLOG

For this assignment, the DOE experimental data using the CATAPULT that my group have conducted during the practical. I will be using FULL FACTORIAL DATA.

DOE PRACTICAL TEAM MEMBERS :

1. Cheryl (Iron Man) – runs #1 and #3

2. Hong Yi (Thor)

3. Kieron (Captain America)

4. Ruba (Black Widow)

 

Data collected for FULL factorial design using CATAPULT A (fill this according to your DOE practical result):


 

 

For Iron Man, Thor, Hulk. USE THIS TEMPLATE TABLE and fill all the blanks

The QUESTION

To determine the effect of _____ projectile weight ____ on the flying distance of the projectile

Scope of the test

The human factor is assumed to be negligible. Therefore, different users will not have any effect on the flying distance of the projectile.

 

Flying distance for the catapult is collected using the factors below:

Arm length =  __12.5_cm

Projectile weight = __0.85___ grams and __2.06____ grams

Stop angle = ___49__ degree

 

Step 1:

State the statistical Hypotheses:

State the null hypothesis (H0):

 

The changes in projectile weight from 0.85g to 2.06g have no difference on flying distance.

 

State the alternative hypothesis (H1):

 

The changes in projectile weight from 0.85g to 2.06g changes the flying distance.

 

 

 

 

Step 2:

Formulate an analysis plan.

Sample size is __n=8__ Therefore t-test will be used.

 

 

Since the sign of H1 is __+__, a left/two/right tailed test is used.

 

 

Significance level (α) used in this test is _0.05___

 

 

Step 3:

Calculate the test statistic

State the mean and standard deviation of Run # _1_:

 

Mean = 153.3

Standard deviation =2.85

 

State the mean and standard deviation of Run #_3_:

 

Mean = 113.8

Standard deviation = 4.05

 

 

Compute the value of the test statistic (t):


 



 

 

 

Step 4:

Make a decision based on result

Type of test (check one only)

1.     Left-tailed test: [ __ ]  Critical value tα = - ______

2.     Right-tailed test: [ __ ]  Critical value tα =  ______

3.     Two-tailed test: [ _v_ ]  Critical value tα/2 = ± ____2.145__

 

Use the t-distribution table to determine the critical value of tα or tα/2



 

Compare the values of test statistics, t, and critical value(s), tα or ± tα/2

tα/2 = +2.145 or -2.145

t = +21.106 or -21.106

Therefore Ho is ____rejected_______ as it reaches the rejection region.

 

 

Conclusion that answer the initial question

 

Since 21.106 is in the rejection region, H0 (where projectile weight has no change in distance) is rejected and H1 (where projectile weight has significant change in distance) is accepted. This shows that the change in projectile weight would result in a significant change in flying distance.

 

 

 

Compare your conclusion with the conclusion from the other team members.

 

My groupmates and I have similar conclusions where changing the projectile weight changes the flying distance largely.

What inferences can you make from these comparisons?

 

From the runs compared between my groupmate and I, factor C remains unchanged (-) while the only factor that changed from high/low were A and B. However, the conclusion made by both our hypothesis was the same, in which changing the projectile weight changes the flying distance largely. Hence it can be inferred that there is little interaction between the A and B factors as changing the high/low values of them would still result in similar outcomes.

Your learning reflection on this Hypothesis testing activity

 

During this lesson on hypothesis testing, the biggest challenge I faced was that it took me a while to understand how it works. There are many formulas to find a specific value that is then used together to determine if the hypothesis is true or false. However, after doing my research, this hypothesis testing method has shown me how to prove a hypothesis right/ wrong. It has also shown me how DOE from the previous practical advances into the next stage. I strongly believe that I would use this method in future experiments that require me to work with several data and sample sizes. It can also be implemented to further improve the tea maker which my group is working on. This would allow me to efficiently analyse data collected, saving time and energy while still producing reliable results/ conclusions.

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