Data Science

Confounder Variable  A confounder  is a variable that is related to both the independent and dependent variable, and partially,  or even entirely, accounts for the relationship between these two. An important thing to note about confounders, is that they  are not included in the hypothesis and they are generally not measured.  This makes it impossible to determine what the actual effect of a confounder was. The only thing to do is to repeat the study, and control the confounder  by making sure it takes on the same value for all participants. Example If we want to estimate house price and in our data set we have those variables : Size  Number of bedrooms  Address ZipCode Age of house  We might find that size is strongly correlated to the price of the house, but in our dataset, the size also correlated to the zip code. and if we loop deeper we might find that the size of the hou...

Post Hoc Tests For ANOVA In the case where the explanatory variable represents more than two groups, a significant ANOVA does not tell us which groups are different from the others. To determine which groups are different from the others, we would need to perform a post hoc test. A post hoc test conducts post hoc paired comparisons. Post hoc means after the fact. And these post hoc paired comparisons must be conducted in a particular way in order to prevent excessive type 1 error. Type 1 error, as you'll recall, occurs when you make an incorrect decision about the null hypothesis. That is, you reject the null hypothesis when the null hypothesis is true. Why can't we just perform multiple ANOVAs? As you know, we accept significance and reject the null hypothesis at P less than or equal to 0.05. A 5% chance that we're wrong and have committed a type 1 error. There's actually a 5% chance of making a type 1 error for each analysis of variance ...

Steps in hypothesis testing  Specify the null (H0) and the alternate hypothesis (H1). Choose a sample. Assess the evidence.  Draw conclusions. Def : Assessing evidence provided by the data, in favor of or against each hypothesis about the population.