Introduction The more advanced methods in statistics have generally been developed to answer real-world questions, and ANOVA is no different. How do we answer questions in the real world, as to which route from home to work on your daily commute is easier, or How would you know which air-conditioner to choose out of a […]Read more "Two Way ANOVA in R"
Outliers are points in a data set that lie far away from the estimated value of the centre of the data set. This estimated centre could be either the mean, or median, depending on what kind of point or interval estimate you’re using. Outliers tend to represent something different from “the usual” that you might […]Read more "Simple Outlier Detection in R"
Not all data in this world is predictable in the exact same way, of course, and not all data can be modeled using the Gaussian distribution. There are times, when we have to make comparisons about data using one of many distributions that represent data which could show different patterns other than the familiar and […]Read more "Comparing Non-Normal Data Graphically and with Non-Parametric Tests"
In my earlier posts on hypothesis testing and confidence intervals, I covered how there are two hypotheses – the default or null hypothesis, and the alternative hypothesis (which is like a logical opposite of the null hypothesis). Hypothesis testing is fundamentally a decision making activity, where you reject or fail to reject the default hypothesis. […]Read more "Power, Difference and Sample Sizes"
Businesses are increasingly beginning to use data to drive decision making, and are often using hypothesis tests. Hypothesis tests are used to differentiate between a pair of potential solutions, or to understand the performance of systems before and after a certain change. We’ve already seen t-tests and how they’re used to ascribe a range to […]Read more "Hypothesis Tests: 2 Sample Tests (A/B Tests)"