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I agree with @hlsmith: use all the data + t-test + quantile regression. Precisely because the group sizes are so big, the Central Limit Theorem guarantees validity of t-test. You may also run two-sample Kolmogorov-Smirnov test to see if the distribution in the test group is the same as that in...
2. ### Timeseries Multiplicative Triple Forecasting model

General observation: Excel is a primitive package. There is much more time series functionality in packages like R, Matlab, Stata and EViews. This functionality will help you run diagnostic tests on the estimated model and extend the model accordingly. In particular, you may want to focus on the...
3. ### Trying to determine attrition

This seems to be a case of survival analysis in discrete time. In particular, the Kaplan-Meier estimator of the survival curve, alongside the corresponding confidence band, may be of use.
4. ### Help with data analysis plan for dissertation

To the best of my knowledge, the PROCESS add-on assumes normally distributed residuals. If they are not normally distributed and the sample size is modest, you are better off estimating various models with interactions using standard SPSS functionality (standard SPSS edition). In many "linear"...
5. ### Which Statistical Test To use?

Stata is fine.
6. ### Which Statistical Test To use?

For each dependent variable, you can estimate ARMAX time series models. Before entering the dependent variable (e.g. Net Interest Income) and the independent variable (Interest Rate) into a particular model, you have to transform them to make them stationary. In other words, if a given variable...

8. ### Determining sub-period probability from overlapping temporal probabilities

This probability cannot be determined without making extra modeling assumptions. It is customary to model the number of rare events like thunders in a given time window via non-homogeneous Poisson process.
9. ### Questionnaire Data - which stats test

Focus on the beginning of the first post, where various tests are listed. Then you can look them up separately in Wikipedia or an introductory statistics textbook. Is there a Layman's guide? Yes: an introductory statistics textbook. One example: Freedman, D., Pisani, R., & Purves, R. (2007)...
10. ### Fit review for multiple systems

In general, you can perform estimation in a loop using R, Matlab or Stata. And then, you can aggregate residuals over systems for each configuration and compare the 6 configurations using a measure like BIC (Bayesian Information Criterion). However, in your situation 8-9 data points are not...
11. ### HW Question: Log-Likelihood Function

Plot the log-likelihood that you have derived and see if you notice anything unusual. Visualization is almost always an important step in diagnostics.
12. ### Repeated measures in SYSTAT 12

Yes. You can look up my web-site in my profile and write to me there. Regards.

14. ### Regression with no intercept - null assumption for

If you are discussing a test for the slope coefficient (b1), then in a linear regression with no intercept H0: y = epsilon, H1: y = b1 * x + epsilon, where epsilon is a random error (residual).
15. ### One way ANOVA or Two Way ANOVA?

Yes, that is true. But is the cell material different between the days? Please check with the professor.
16. ### One way ANOVA or Two Way ANOVA?

Are different drumsticks tested on different days or are they the same for each preservative?
17. ### Is ANOVA right for me?

Your experiment is a case of Repeated Measures ANOVA if the residuals are normally distributed. The normality can be verified using Kolmogorov-Smirnov, Shapiro-Wilk or another test. If the residuals are not normally distributed, you should use a nonparametric version of Repeated Measures ANOVA...
18. ### Moment generating function

Use the fact that E[Y^k] is the k-th derivative of the moment generating function evaluated at t = 0.
19. ### Using Residuals to Make Conclusions

So analyze the plot for the distributional properties I mentioned (symmetry / asymmetry, tails, etc). To check unimodality, you may use histograms.
20. ### Confidence intervals for proportions

No. A CI for 1/r is to be obtained algebraically from the CI for r.