Hypothesis Testing
HYPOTHESIS TESTING TASK FOR INDIVIDUAL BLOG
For this assignment, you will use the DOE
experimental data using the CATAPULT that you have conducted during the
practical. You will use FULL FACTORIAL DATA. You are free to express yourself
in your blog, but the table provided on page 2 to 7 must be followed.
DOE PRACTICAL
TEAM MEMBERS (fill this according to your DOE practical):
1. Lee Yeung Juen (Iron
Man)
2. Mavis Chin (Thor)
3. Isabelle (Captain
America)
4. Alvin Chuah (Black Widow)
Data collected for FULL factorial design using CATAPULT A (fill this according to your DOE practical result):
Iron Man will use Run #1 and Run#3. To
determine the effect of projectile weight.
Thor will use will use Run #2 and Run#4. To
determine the effect of projectile weight.
Captain America will use Run #2 and Run#6.
To determine the effect of stop angle.
Black Widow will use Run #4 and Run#8. To
determine the effect of stop angle.
Hulk will use Run #3 and Run#5. To
determine the effect of projectile weight
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The QUESTION |
To determine the effect of ___projectile weight___ on the flying
distance of the projectile |
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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
= _25___cm Projectile
weight = __20___ grams and __0.85____ grams Stop angle =
__15___ degree |
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Step 1: State the statistical Hypotheses: |
State the null
hypothesis (H0): State the
alternative hypothesis (H1): The projectile weight has a significant effect on the flying distance of the projectile. |
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Step 2: Formulate an analysis plan. |
Sample size is
_n=8__ 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_ |
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Step 3: Calculate the test statistic |
State the mean
and standard deviation of Run # _1_: State the mean
and standard deviation of Run #_3_: Standard deviation = 5.46 cm Compute the value of the test statistic (t): v = 8 + 8 - 2 = 14 |
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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 t = ± 8.6054 Therefore Ho is __rejected___. |
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Conclusion that answer the initial question |
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Compare your conclusion with the conclusion from the other team
members. |
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What inferences can you make from these comparisons? |
For runs 2 and 4, Factor A, arm length, is positive. For runs 1 and 3, the factor is negative. Both tests result in Ho being rejected and H1 being accepted, however, a negative factor A produces a test statistic value of ± 8.6054 while a positive factor A produces a value of ± 3.085. This shows us that a change in factor A results in a significant change in the test statistic, there is a significant interaction between factors A and B. |
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Your learning reflection on this Hypothesis testing activity |
The hypothesis testing activities have taught me a better way to verify my hypothesis for experiments. This will be very important for my internship and final-year project as I would be carrying out many experiments with a myriad of data sample sizes. With knowledge in hypothesis testing, I would be able to analyse the results I've collected with minimal errors and produce more reliable work. |
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