Hypothesis testing (IRON MAN)

Hi guysss, in today's blog, I'm going to be sharing with you on hypothesis testing! Don't get a headache when you see the numbers below HAHA. It's all just part of the process to analyze if my claim is true or false. These data are collected from the previous practical where we recorded the flying distance of the projectile weight, if you want to find out more you can read up on my previous blog.

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

I have chosen to be Iron Man. To analyze this data, Iron Man will use Run #1 and Run#3. To determine the effect of projectile weight.

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 user will not have any effect on the flying distance of projectile. Flying distance for catapult is collected using the factors below: Arm length = _28.1_cm Projectile weight = __0.86___ grams and _2.05_____ grams Stop angle = 120 degree
​Step 1: State the statistical Hypotheses:	State the null hypothesis (H0): At an arm length of 28.1 cm and stop angle of 120 degrees, the flying distance of the projectile using a projectile weight of 0.86g and 2.05g has no difference. State the alternative hypothesis (H1): At an arm length of 28.1 cm and stop angle of 120 degrees, the flying distance of the projectile using a projectile weight of 0.86g and 2.05g are different.
​Step 2: Formulate an analysis plan	Sample size is 16_ Therefore t-test will be used. Since the sign of H1 is _≠ , a two-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= 305.6 s= 3.34 State the mean and standard deviation of Run #_3_: Mean= 254.3 s=3.58 Compute the value of the test statistic (t):
Step 4: Make a decision based on result	Type of test (check one only) Two-tailed test:[ t=8.92 ] Critical value tα/2= ± _4.303__ 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/2 Therefore Ho is rejected.
Conclusion that answer the initial question	​Since the test statistic, t = 8.92 lies in the rejection region, the null hypothesis is rejected. Hence, At an arm length of 28.1 cm and stop angle of 120 degrees, the flying distance of the projectile using a projectile weight of 0.86g and 2.05g are different.
Compare your conclusion with the conclusion from the other team members.	​Asraf: To conclude, there will be significant difference of the distance. The lighter the projectile weight, the further the distance will be. Since Ho is false, H1 is true Valarie: In conclusion, using a higher stop angle will result in a higher flying speed of the distance of the projectile while using a lower stop angle will result in a lower flying speed distance of the projectile. Therefore, since Ho is rejected, H1 is true. Eshvin: ​In summary, when a high stop angle is used, the flying distance of the projectile will be high. When a low stop angle is used ,the flying distance of the projectile will be low. Thus Ho is rejected.
What inferences can you make from these comparisons?	​From these comparisons, I can infer that from all three results, their alternative hypothesis (H1) is true while their null hypothesis (Ho) is false. For Asraf, since he analyzed that the lesser projectile weight will result in further flying distance, while for me I concluded that the projectile weight will affect the flying distance. Since our conclusion matched, therefore I can conclude that our alternative hypothesis is true. For Valarie and Eshvin, they have both concluded that when a higher stop angle is used, the flying distance of the projectile is. Since their results matched, I can infer that their alternative hypothesis is true.
Your learning reflection on this Hypothesis testing activity	​In this hypothesis testing activity, i learned that Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data. The test provides evidence concerning the plausibility of the hypothesis, given the data. Statistical analysts test a hypothesis by measuring and examining a random sample of the population being analyzed. Before this activity i wondered, why is hypothesis testing so important? Then i realised hypothesis testing is one of the most important concepts in statistics because it is how you decide if something really happened, or if certain treatments have positive effects, or if groups differ from each other or if one variable predicts another. In short, you want to proof if your data is statistically significant and unlikely to have occurred by chance alone. In essence then, a hypothesis test is a test of significance.

That is all for today's blog, stay tuned for the next blog byee.