Recent content by Miner

  1. Miner

    P-value of intercept = 0 meaning? Can age be independent var in simple regression?

    This outlier is an indication that as the cars get that old, the linear portion of the regression becomes nonlinear (starting around 10 years) and asymptotic to zero. Car prices cannot go negative. For classic cars the value may even increase as it gets older.
  2. Miner

    P-value of intercept = 0 meaning? Can age be independent var in simple regression?

    From years of hands-on application in industry, I would say yes, it is fine. Statistical purists will probably disagree, but I have found in the real world, you can safely bend (not break) a lot of assumptions. However, in industrial statistics, I can also verify what works in practice. In...
  3. Miner

    P-value of intercept = 0 meaning? Can age be independent var in simple regression?

    The vertical lines are caused by the fact that age is probably in integer form rather than truly continuous. That causes the residuals to group together on the x-axis rather than spread out.
  4. Miner

    simple count - type of data

    Counts are counts, not nominal. You can have binary, nominal or ordinal 'categories' with counts for each category. Counts would normally follow a Poisson distribution, but with 50 possible levels, it becomes pseudo-continuous data and you should be able to use a t-test. You could also...
  5. Miner

    Two quick questions about correlation coefficients

    Two possibilities are having a lot of scatter in the data and a nonlinear relationship. Have you plotted the raw data using a scatter plot? Does it look like a shotgun blast pattern? A nonlinear relationship (try a Spearman's rho correlation)?
  6. Miner

    Help writing hypotheses!

    The null hypothesis is typically the status quo (e.g., the treatment has no effect, there is no difference/correlation, the coefficient is zero, etc.), while the alternate hypothesis is the opposite (e.g., the treatment does have an effect, there is a difference/correlation, the coefficient is...
  7. Miner

    Hierarchical clustering? Ward's linkage? K-mean clustering? anova?

    I did some research on linkage and distance methods in the past. The attached is a distilled summary of that. Regarding the sample sizes. Reliability will depend on the separation between clusters. If they are widely separated, a relatively small sample will suffice. As the separation...
  8. Miner

    Income Inequality Data

    Is this what you are looking for?
  9. Miner

    What model to estimate the prices of used cars?

    There will also be a discontinuity in the regression caused by the supply chain disruption in electronic chips used in new cars. The price of used cars skyrocketed when new cars could not be built.
  10. Miner

    wheres my cat?

    As soon as I read fed2's post I was waiting for this shoe to drop.
  11. Miner

    The most appropriate method in this case

    Why? Your stated goal was to determine the cause of death for machines that have live more than 1500 days. Regression of any type will not provide this information. Always include all of your available data when performing a reliability analysis. Excluding the data less than 1500 days will...
  12. Miner

    The most appropriate method in this case

    I think using Cox regression is an overkill solution. Your stated goal was to determine the cause of death for machines that have live more than 1500 days. A simple Pareto chart of the 900 will provide this information. The one surviving machine will not change your conclusions. Just because...
  13. Miner

    F test significant but simple contrasts not

    An ANOVA is an omnibus test. It does not actually test all possible contrasts, but effectively tests the largest effect. You only know that one of the contrasts is significant. That is why you need Post Hoc tests to determine which contrast(s) are the cause.
  14. Miner

    F test significant but simple contrasts not

    Yes. Assuming t0 = 1, t1 = 2, ..., Brett is testing the logical contrasts. However, it is possible that the change over time was not linear, an unaccounted covariate affected the measurements for some time periods, etc. resulting in a different contrast having a larger impact.
  15. Miner

    F test significant but simple contrasts not

    That is one possibility. A second possibility is that there is another, stronger contrast that is driving the main effect.