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Stat Your Way
Registrace 3. 12. 2014
Dive into the world of statistics with Stat Your Way, a comprehensive video channel designed specifically for doctoral students and novice researchers. Whether you're embarking on your academic journey or seeking to refine your research skills, our channel is your go-to resource for all things statistics.
Understanding Mediation Testing and Indirect Effects
Mediation testing is a statistical method used to understand the mechanism through which an independent variable affects a dependent variable via a third variable, known as the mediator. This process helps in revealing how and why certain effects occur, providing deeper insights into causal relationships.
What is Mediation?
Mediation occurs when the relationship between an independent variable (IV) and a dependent variable (DV) is explained by a third variable (mediator, M). The mediator serves as an intermediary process through which the IV influences the DV.
Components of Mediation
1. Independent Variable (IV): The variable that is manipulated or considered the cause.
2. Mediator (M): The variable that transmits the effect of the IV on the DV.
3. Dependent Variable (DV): The outcome or the effect that is being measured.
Mediation testing and indirect effects provide a nuanced understanding of the relationships between variables, helping researchers uncover underlying mechanisms in causal pathways. By identifying mediators, we can better comprehend how and why certain effects occur, leading to more effective interventions and policies.
What is Mediation?
Mediation occurs when the relationship between an independent variable (IV) and a dependent variable (DV) is explained by a third variable (mediator, M). The mediator serves as an intermediary process through which the IV influences the DV.
Components of Mediation
1. Independent Variable (IV): The variable that is manipulated or considered the cause.
2. Mediator (M): The variable that transmits the effect of the IV on the DV.
3. Dependent Variable (DV): The outcome or the effect that is being measured.
Mediation testing and indirect effects provide a nuanced understanding of the relationships between variables, helping researchers uncover underlying mechanisms in causal pathways. By identifying mediators, we can better comprehend how and why certain effects occur, leading to more effective interventions and policies.
zhlédnutí: 12
Video
UnderstandingCorrelation
zhlédnutí 15Před 14 dny
Correlation is a statistical measure that expresses the extent to which two variables are linearly related. It quantifies the degree to which changes in one variable predict changes in another. Here’s a detailed introduction to understanding correlation: Interpreting Correlation Coefficients 0.9 to 1.0 (or -0.9 to -1.0): Very high correlation 0.7 to 0.9 (or -0.7 to -0.9): High correlation 0.5 t...
Conducting the Mann-Whitney U Test Using SPSS
zhlédnutí 432Před 21 dnem
The Mann-Whitney U test, also known as the Mann-Whitney-Wilcoxon (MWW) test or Wilcoxon rank-sum test, is a non-parametric test used to determine whether there is a significant difference between the distributions of two independent groups. It is often used as an alternative to the t-test when the assumptions of the t-test, such as normality of the data, are not met. Key Features of the Mann-Wh...
How to Run a Paired T-test in SPSS
zhlédnutí 424Před 21 dnem
The paired t-test is a statistical method used to compare two related samples to determine if there is a significant difference between their means. This test is particularly useful in situations where the same subjects are measured before and after a treatment or intervention, or when two related observations are made on the same subject.
Moderation Analysis: Exploring Interaction Effects
zhlédnutí 73Před 2 měsíci
Moderation analysis, also known as interaction analysis, is a statistical technique used in research to examine whether the relationship between two variables (the independent variable and the dependent variable) changes depending on the level of a third variable (the moderator). In essence, moderation analysis explores whether the effect of the independent variable on the dependent variable va...
How to run a Discriminant Analysis using SPSS
zhlédnutí 251Před 3 měsíci
Discriminant Analysis is a statistical technique used to classify observations into groups based on their characteristics or features. It's particularly useful when you have a set of observations and you want to classify them into predefined categories or groups based on a set of continuous predictors or features. Here's how it generally works: Data Collection: Gather data on several variables ...
Testing Assumptions for Discriminant Analysis using SPSS
zhlédnutí 102Před 3 měsíci
Discriminant Analysis (DA), also known as Discriminant Function Analysis, is a statistical technique used for classification and prediction of group membership. It is particularly useful when the dependent variable is categorical, and the independent variables are continuous. The goal of Discriminant Analysis is to find the best combination of independent variables that can distinguish between ...
Assumptions for Factor Analysis
zhlédnutí 179Před 3 měsíci
Testing assumptions for factor analysis is crucial to ensure the validity and reliability of the results. By testing these assumptions, researchers can ensure the robustness and validity of their factor analysis results. If assumptions are violated, appropriate corrective measures such as data transformation, removing outliers, or using alternative factor analysis methods may be necessary.
On Being Misled by Numbers
zhlédnutí 86Před 4 měsíci
"On Being Misled by Numbers" is a phrase that encapsulates the idea that numerical data, if not interpreted carefully and critically, can lead individuals to erroneous conclusions or misunderstandings about a situation or phenomenon. It underscores the importance of statistical literacy and critical thinking skills in evaluating and interpreting numerical information. This concept is particular...
Misleading Graphs
zhlédnutí 44Před 4 měsíci
Misleading graphs are graphical representations of data that intentionally or unintentionally distort the information they are supposed to convey. They can be designed to mislead viewers by exaggerating or downplaying certain aspects of the data. Here are some common techniques used to create misleading graphs:Truncated Axes: This involves excluding a portion of the axis to exaggerate differenc...
Creating fictitious data USING SPSS
zhlédnutí 156Před 4 měsíci
Fictitious data" in SPSS refers to data that is created artificially for testing, demonstration, or simulation purposes. This type of data is not based on real-world observations but is generated to mimic realistic data patterns and distributions. Fictitious data is commonly used in various scenarios, including: Testing Analysis Techniques: Researchers and analysts may generate fictitious data ...
How to conduct Binary Logistic Regression using SPSS
zhlédnutí 95Před 11 měsíci
Binary logistic regression is the statistical technique used to predict the relationship between the dependent variable (Y) and the independent variable (X), where the dependent variable is binary in nature.
Testing the Assumptions for Binary Logistic Regression using SPSS
zhlédnutí 3,2KPřed 11 měsíci
Binary logistic regression is the statistical technique used to predict the relationship between the dependent variable (Y) and the independent variable (X), where the dependent variable is binary in nature. Independence of observations. Categories of the outcome variable must be mutually exclusive and exhaustive. Linear relationship between continuous variables and the logit transformation of ...
How to conduct a One Sample Chi Square test using SPSS
zhlédnutí 136Před 11 měsíci
The one-sample chi-square test evaluates whether the proportions of individuals who fall into categories of a variable are equal to hypothesized values.
How to conduct a Contingency Chi Square using SPSS
zhlédnutí 60Před 11 měsíci
A two-way contingency table analysis evaluates whether a statistical relationship exists between two variables.
How to conduct an exploratory factor analysis using SPSS
zhlédnutí 1,3KPřed 6 lety
How to conduct an exploratory factor analysis using SPSS
Testing Assumptions for Multiple Regression using SPSS
zhlédnutí 39KPřed 7 lety
Testing Assumptions for Multiple Regression using SPSS
The Relationship between Multiple Regression and ANOVA
zhlédnutí 1,9KPřed 7 lety
The Relationship between Multiple Regression and ANOVA
How to conduct a multiple regression analysis using spss
zhlédnutí 6KPřed 7 lety
How to conduct a multiple regression analysis using spss
How to run a one-way Multivariate Analysis of Variance .
zhlédnutí 66Před 7 lety
How to run a one-way Multivariate Analysis of Variance .
Testing the assumptions for ANCOVA using SPSS
zhlédnutí 6KPřed 7 lety
Testing the assumptions for ANCOVA using SPSS
How to conduct a one-way analysis of covariance using spss
zhlédnutí 224Před 7 lety
How to conduct a one-way analysis of covariance using spss
How to run a two way analysis of variance using SPSS
zhlédnutí 80Před 7 lety
How to run a two way analysis of variance using SPSS
How to run a one-way analysis of variance using SPSS
zhlédnutí 59Před 7 lety
How to run a one-way analysis of variance using SPSS
How to run a one sample t-test using SPSS
zhlédnutí 106Před 7 lety
How to run a one sample t-test using SPSS
Can i have a link to the data set I want to download it
Thanks so much George
You saved my thesis
Mr.G, 1-5,....the 1way analysis for covariance demonstrates the flow between affects and the control group,...the sample is relevant as what % of the total population...are there any degrees of freedom....
Very good!
good sir
Thank you, professor, it was a great takeaway from your teaching.
you can add text what you are talking about to make it clear explanation
Please speak clearly
Very good information.
Hi, thanks for the video, great help! Could you please explain why you want a minimum of a .2 correlation for predictor variables and DV, and what should you do if correlation is lower? Both of my predictors correlate at .19 with the DV, is it a close enough type scenario?
Qqq
how did you check for normality?
Please review between 5:50 to 6:67 of the video.
Hello Dr. Bradley! I have a question. What do we need to do when the variances are unequal?
good question
Thanks man, really appreciated this video it helped