전체 글
-
One way ANOVA-post hoc t-tests and Factorial ANOVAInferential Statistics from Amsterdam 2021. 6. 24. 10:32
What I'm going to do in this blog is talking about one way ANOVA-post hoc t-tests and factorial ANOVA. 1. One way ANOVA-post hoc t-tests : it just means how to follow up a significant F-test in one way ANOVA with pairwise comparisons of group means using pairwise t-tests or confidence intervals. They tell us which group means differ significantly and in what direction. 1-1) Follow up comparisons..
-
Null space and column space basisVector and Space 2021. 6. 23. 15:44
What I want to share in this blog is a basis of null space and column space. 1. a null space and a column space: I told you these in an earlier blog, but I'm going to talk about these again for a quick review. the null space is a set that contains vectors that make an equation a matrix A times a vector x 0. Here it is. column space is a lot easier to understand, which is a set of column vectors ..
-
One way ANOVA and Assumptions and F-testInferential Statistics from Amsterdam 2021. 6. 23. 09:54
What i want to talk about in this page is One way ANOVA and assumptions and F-test for one way ANOVA. 1. One way ANOVA : Analysis of variance(known as ANOVA) allows us to compare means of more than two groups. It's a method of analysis we use in research designs with a quantitative response variable and one or more independent variables. One way ANOVA uses one response variable and independent v..
-
Categorical response variableInferential Statistics from Amsterdam 2021. 6. 22. 09:43
In this blog, i'm going to talk about categorical response variable. 1. Categorical response variable : Until now, I looked at regression models that describe or predict a quantitative variable, but there are also regression models for ordinal and nominal response variable. 1-1) logistic function : The logistic function has a sigmoid shape or s curve. This produces estimated values that lie betw..
-
Column space of a matrixVector and Space 2021. 6. 21. 10:24
In this blog, i'm going to talk about column space of a matrix. 1. column space : the column space is all the possible linear combinations of column vectors in a matrix. It definitely contains the 0 vector, is closed under any scalar multiplication and addition. ** Note that a matrix is just a way of writing a set of column vectors. 2. Another way to view it : If Ax is equal to that, and I'm say..
-
Checking assumptions and Categorical predictorsInferential Statistics from Amsterdam 2021. 6. 21. 09:46
In this blog, I'm going to talk about assumptions and categorical predictors. 1. Checking assumptions : when i dealt with linear regression, i said that there are 4 assumptions to have to be met, which were linearity, normliaty, homoscedasticity and independence. Here, it also requires assumptions to use the test. Here, i'm going to check what assumptions there are. 1-1) Linearity : the relation..
-
Null space : Linear IndependenceVector and Space 2021. 6. 3. 15:39
In this blog, i'm going to talk about a null space when column vectors in a matrix are linearly independent. 1. Linear Independence : Before we get into the topic, I want to review the definition of linear independence quickly. The linear independence is vectors in a set that cannot be represented by any linear combination of the other vectors. The null space is a set of vectors that satisfies t..
-
Overall test and Individual testsInferential Statistics from Amsterdam 2021. 6. 3. 15:02
In this blog, i'm going to talk about overall test and individual tests. 1. Overall test : This is also referred to as the overall F-test of a multiple regression model. An overall test helps us decide whether predictors are related to the response in the population. 1-1) hypotheses : we also specify the null hypothesis when we conduct overall test. If there's no relation between the predictors ..