# Recent content by Miner

1. ### Which hypothesis test to use to compare two lab tests?

Here are the A vs. B comparisons. Again, the equivalence limits were arbitrarily chosen by me. You need to decide what these should be.
2. ### How do I analyze data to find points where there is a "significant" increase in the "y" variable.

Is this the concept?
3. ### 2-way ANOVA p-value output

I agree with Karabiner. Statistical significance only means that the effect is large RELATIVE TO the experimental error. It does NOT mean that it is of any practical importance. Small p-values can occur, as Karabiner said, from very large sample sizes, or where the experiment deliberately...
4. ### 2-way ANOVA p-value output

Other than the fact that they are extremely small (p<<<<<<<< 0.05), you have taken them out of context, so we cannot explain more than that. Note: e-16 is scientific notation indicating that the decimal has been shifted 16 spaces to the right (e.g., 1e-5 = 0.00001).
5. ### Which hypothesis test to use to compare two lab tests?

There are several options. You can use a Bland-Altman plot, a gauge linearity and bias study, and a paired equivalence test. Attached are examples of each. NOTE: On the equivalence test, you have to define equivalence limits. These are the limits at which there is no practical difference...
6. ### Time Series Analysis

What is your question?
7. ### How do I analyze data to find points where there is a "significant" increase in the "y" variable.

Are you looking to determine when is a shift in X large enough to be seen past the prediction error in Y?
8. ### Limits of agreement and Bland Altman plot

I recommend the Limits of Agreement (mean difference +/- 1.96 StDev of differences), and the bias (plus any relationship between bias and size of measurement).
9. ### Variation in data

Given that we are discussing organic systems that degrade over time, a reliability analysis method called degradation analysis comes to mind.
10. ### Time series

Q1 - Because linear time series models are only designed to model linear trends in time series data. Q2 - You may also have exponential trends (read COVID-19) and s-curve trends. Q3 - You may have seasonality (additive or multiplicative) and cyclicity, none of which a linear model can...
11. ### Predictor

You can still analyze it as continuous data, but it may show up as "chunky" on normality or residual plots. This can throw off the p-values in a normality test even though all the data points fall along a straight line. It may violate all sorts of assumptions and prevent you from publishing in...
12. ### Predictor

This is probably due to round-up to fewer decimal places. Can you gain access to the data used to calculate the rates?
13. ### Regression Analysis without Excel or other program

When you set the const to TRUE, the equation fit is y = b + mx. When const is set to FALSE, b is forced to zero and the equation that is fit is y = mx. Coefficient is m.
14. ### Test significant difference question

You can still use a t-test for unequal variances.
15. ### one numerical and three categorical variables - which test?

If I understand your study design correctly, you have one categorical independent variable (Water Source type), which has three levels, and one continuous dependent variable (distance). A 1-way ANOVA would be a good place to start. BTW, how do you know whether the water sources today are the...