Question

Since it is a 3 factor experiment, there are a total of 8 combinations. There are two replications per combination so there are a total of 16 data points. Analyze the data, determine which factors and interactions are significant, and build a model to predict the throw distance.

Low High Factor A: Pull back angle 140 160 Factor B: Tower Pin 2nd from top Top Factor C: Stopping pin 3rd from front4th from front Run A B -1 1 1 с -1 -1 1 1 -1 - 1 - 1 - 1 1 - 1 1 -1 - 1 - 1 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 output 69 74.5 60.5 56.5 69.5 75.5 63 67.5 57.5 66 68.5 69.5 62.5 60.5 68 65.5 -1 - 1 - 1 1 - 1 - 1 1 1 - 1 -1 -1 -1 - 1 1 - 1 1 - 1

Answer 1

I have do this problem with the help of SPSS

x ta *Untitled1 [DataSetO] - IBM SPSS Statistics Data Editor File Edit View Data Transform Analyze Graphs Utilities Extensions Window Help A 14 HHH 17: OUTPUT Visible: 4 of 4 Variables B var var var var var var var var var var var var 1 2 BA 1.00 1.00 -1.00 -1.00 1.00 3 -1.00 1.00 1.00 -1.00 -1.00 4 5 OUTPUT 69.00 74.50 60.50 56.50 69.50 75.50 63.00 67.50 57.50 66.00 6 &c -1.00 -1.00 1.00 1.00 1.00 -1.00 -1.00 1.00 1.00 -1.00 -1.00 1.00 -1.00 1.00 -1.00 1.00 7 8 1.00 -1.00 -1.00 1.00 1.00 -1.00 -1.00 1.00 9 10 11 -1.00 1.00 -1.00 1.00 -1.00 68.50 69.50 12 13 14 1.00 -1.00 -1.00 15 16 17 1.00 -1.00 1.00 62.50 60.50 68.00 65.50 1.00 1.00 -1.00 18 19 20 21 22 23 Data View Variable View IBM SPSS Statistics Processor is ready Type here to search е Unicode:ON 20:43 A) ENG 16-05-2020 D

x HHH Visible: 4 of 4 Variables var var var var var var var var 1 Univariate X Dependent Variable: OUTPUT Model. Contrasts... Fixed Factor(s): Plots.. B Post Hoc.. EM Means. Random Factor(s): ta *Untitled1 [DataSetO] - IBM SPSS Statistics Data Editor File Edit View Data Transform Analyze Graphs Utilities Extensions Window Help Reports A 14 Descriptive Statistics 17: OUTPUT Bayesian Statistics BA &B Tables var var var 1.00 -1.00 Compare Means 2 1.00 1.00 General Linear Model GLM Univariate.. 3 -1.00 1.00 Generalized Linear Models GM Multivariate... 4 -1.00 -1.00 Mixed Models SEM Repeated Measures... 5 1.00 -1.00 Correlate 6 1.00 1.00 Variance Components... Regression 7 -1.00 -1.00 Loglinear 8 -1.00 1.00 Neural Networks 9 1.00 -1.00 Classify 10 1.00 1.00 Dimension Reduction 11 -1.00 -1.00 12 -1.00 Scale 1.00 13 1.00 Nonparametric Tests -1.00 14 1.00 1.00 Forecasting 15 -1.00 -1.00 Survival 16 -1.00 1.00 Multiple Response 17 Missing Value Analysis... 18 Multiple Imputation 19 Complex Samples 20 Simulation... 21 Quality Control 22 Spatial and Temporal Modeling. 23 Direct Marketing Save... Options... Bootstrap. Covariate(s): WLS Weight: 1 OK Paste Reset Cancel Help Data View Variable View Univariate... IBM SPSS Statistics Processor is ready Unicode:ON 20:44 A) ENG 16-05-2020 Type here to search е D

From the above output
We can see that
P value of factor A is 0.853
The p value is grater than level of significance 0.05
Do not reject H0
So the factor A is insignificant
Like this compare all p value with level of significance

the all p value are grater than the level of significance
Factor B is insignificant
Factor c is also insignificant
Interaction effect AB is insignificant
Interaction effect Bc is insignificant
Interaction effect AC is insignificant
Interaction effect ABC is insignificant