numiqoLogistic regression is a statistical method used for modeling the relationship between a dependent variable and one or more independent variables. It is particularly suited for classification problems, where the dependent variable is categorical. In this Video we will discuss what a Logistic Regression is, how it is calculated and most importantly, how the results are interpreted.
Logistic Regression: An Easy and Clear Beginner’s Guidenumiqo2025-01-14 | Logistic regression is a statistical method used for modeling the relationship between a dependent variable and one or more independent variables. It is particularly suited for classification problems, where the dependent variable is categorical. In this Video we will discuss what a Logistic Regression is, how it is calculated and most importantly, how the results are interpreted.
00:00 What is a Logistic Regression? 6:17 Interpreted the results of a Logistic Regression 12:11 Odds ratio in Logistic Regression 21:13 ROC CurveStandard Deviation (explained in 3 minutes)numiqo2025-10-01 | Standard deviation is a statistical measure of the amount of variation or dispersion in a set of numerical data, indicating how spread out the values are from their mean (average). #statistics #datascience #dataanalysis #dataanalytics #research #thesis #stats #researcher #science #datatab #SPSSWhy two Formulas for Standard Deviation? When and Why use n vs. n−1.numiqo2025-09-28 | Why are there two formulas for standard deviation? In this video, we break down the difference between dividing by n and dividing by n−1—in plain language with simple examples. You’ll learn when to use each formula and why the “n−1” version (Bessel’s correction) is standard when you work with samples.
What you’ll learn: ► Population vs. sample: what’s the difference and why it matters ► Why estimating the mean “uses up” one degree of freedom ► When to divide by n (population) vs. n−1 (sample) ► Clear intuition for degrees of freedom
► E-BOOK numiqo.com/statistics-bookCan we simply say that the standard deviation is the mean of the deviations from the mean?numiqo2025-09-15 | Hi! In this video, we’ll ask: can we simply say that the standard deviation is the mean of the deviations from the mean, or is that an oversimplification?
First, let’s start with something we can all agree on: The standard deviation measures how far values typically deviate from the mean. Ok, but what does that mean? What does typically mean?
► E-BOOK numiqo.com/statistics-bookWe will be renaming soon...numiqo2025-09-10 | We’ve got big news! DATAtab is getting a new name. For reasons I’ll explain in a moment, we’ve decided to rename ourselves. So we’ll soon have a new name, but nothing will change for you—and of course our team will also remain the same. :)ANCOVA (Analysis of Covariance): A Mix of ANOVA and Regressionnumiqo2025-05-26 | ANCOVA (Analysis of Covariance) is a statistical method that combines ANOVA (Analysis of Variance) and regression. It compares the means of different groups while controlling for the effects of one or more continuous variables (called covariates) that might influence the outcome.
In short: ANCOVA adjusts group means by removing the effect of covariates, helping you determine if group differences are still significant after accounting for those variables.
► E-BOOK numiqo.com/statistics-bookxBar-R Chart (Statistical process control)numiqo2025-05-05 | What is an xbar R Chart and how is it calculated? Xbar-R Charts are Control Charts used to monitor and control processes by tracking the performance of key variables over time. They help identify trends, shifts or any unusual patterns that might indicate a problem with the process.
0:00 What is an xbar R Chart? 0:49 Example of an xbar R Chart. 1:29 How to calculate an xbar R Chart? 5:53 How to calculate a R Chart? 5:53 Create an xbar R Chart online with Numiqo?Paired Samples t-Testnumiqo2025-04-08 | What is a paired t-test, how is it calculated, and how are the results interpreted? A paired t-test is a hypothesis test that compares two paired samples.
► Example Data and t-Test Calculator numiqo.com/statistics-calculator/hypothesis-test/paired-t-test-calculator?example=before_afterMulticolinarity - An Easy and Clear Beginner’s Guidenumiqo2025-02-25 | Multicollinearity in regression occurs when two or more independent variables are highly correlated with each other, making it difficult to determine the individual effect of each predictor on the dependent variable. It can inflate the variance of coefficient estimates and make the regression results unstable and difficult to interpret.
Logistic Regression numiqo.com/tutorial/logistic-regressionWilcoxon Test (Wilcoxon signed rank test) Simply explainednumiqo2025-02-13 | The Wilcoxon test is a non-parametric statistical test used to compare paired samples when the data is not normally distributed. The Wilcoxon signed rank test is the non-parametric counterpart to the paired t-test.
Standard Normal Distribution (z-Table) numiqo.com/tutorial/z-distributionBest Data Science YouTube Channels - Your Recommendationsnumiqo2025-02-05 | Discover the best YouTube channels to learn Data Science! 🚀 Whether you're a beginner or an expert, these channels offer top-notch tutorials, insights, and industry trends to boost your skills.
What are Dummy Variables in Regression?numiqo2025-02-03 | Dummy variables in regression are artificial variables created to represent categorical data numerically. They take binary values (0 or 1) to indicate the presence or absence of a particular category. Since regression models require numerical input, dummy variables allow categorical variables (e.g., gender, region, or product type) to be incorporated into the analysis.
Logistic Regression numiqo.com/tutorial/logistic-regressionStatistics - A Full Lecture to learn Data Science (2025 Version)numiqo2025-01-29 | Welcome to our comprehensive and free statistics tutorial (Full Lecture)! In this video, we'll explore essential tools and techniques that power data science and data analytics, helping us interpret data effectively. You'll gain a solid foundation in key statistical concepts and learn how to apply powerful statistical tests widely used in modern research and industry. From descriptive statistics to regression analysis and beyond, we'll guide you through each method's role in data-driven decision-making. Whether you're diving into machine learning, business intelligence, or academic research, this tutorial will equip you with the skills to analyze and interpret data with confidence. Let's get started!
0:00 Intro 1:52 Basics of Statistics 21:56 Level of Measurement 34:56 t-Test 51:18 ANOVA (Analysis of Variance) 1:05:36 Two-Way ANOVA 1:21:51 Repeated Measures ANOVA 1:36:22 Mixed-Model ANOVA 1:48:04 Parametric and non parametric tests 1:55:49 Test for normality 2:03:56 Levene's test for equality of variances 2:08:11 Mann-Whitney U-Test 2:17:06 Wilcoxon signed-rank test 2:28:30 Kruskal-Wallis-Test 2:38:45 Friedman Test 2:49:12 Chi-Square test 2:59:46 Correlation Analysis 3:27:07 Regression Analysis 4:35:31 k-means clustering 4:44:02 Confidence intervalBest YouTube Channels to learn Statisticsnumiqo2025-01-27 | Looking for the best YouTube channels to learn statistics in a fun and easy way? In this video, I share my top picks—from clear and simple explanations to engaging and entertaining lessons. Whether you're a beginner or diving into advanced topics like regression, ANOVA, or machine learning, these channels have you covered!
► Numiqo online Statistical Software numiqo.com/statistics-calculator/regressionRegression Analysis | Full Course 2025numiqo2025-01-21 | This comprehensive YouTube course covers Regression Analysis from the ground up, helping you master the theory, application, and real-world implementation of regression models. Whether you're a beginner looking to understand the basics or an advanced learner seeking to refine your skills, this course will equip you with everything you need to know about regression techniques, statistical modeling, and predictive analytics.
0:00 Intro 1:19 What is Regression Analysis? 7:58 What is Simple Linear Regression? 21:45 What is Multiple Linear Regression? 47:24 What is Logistic Regression?Logistic Regression - Simply explained in 2 minnumiqo2025-01-19 | Logistic regression is a statistical and machine learning technique used for binary classification problems (i.e., when the target variable has only two possible outcomes, like 0 or 1, Yes or No, Spam or Not Spam).
#statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationRegression Analysis - Linear, Multiple and Logistic Regressionnumiqo2025-01-16 | Regression analysis is a set of statistical methods used for the estimation of relationships between a dependent variable and one or more independent variables.
#statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationHierarchical Cluster Analysis - Simply Explainednumiqo2025-01-12 | Hierarchical clustering, also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters.
#Statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationMultiple Linear Regression: An Easy and Clear Beginner’s Guidenumiqo2025-01-08 | Multiple Linear Regression is a statistical technique used to model the relationship between one dependent variable and two or more independent variables. It extends simple linear regression by considering multiple predictors, allowing for more accurate predictions and insights into how each independent variable impacts the dependent variable.
00:00 What is a Multiple Linear Regression? 1:22 What is the difference between Simple Linear and Multiple Linear Regression? 2:25 What is the equation of Multiple Linear Regression? 4:10 What are the assumptions of a Multiple Linear Regression? 12:31 Example for a Multiple Linear Regression. 12:58 How to calculate a Multiple Linear Regression? 13:28 How to interpret a Multiple Linear Regression? 14:00 How to interpret the Regression Coefficients? 16:28 How to interpret the p-Value in a Multiple Linear Regression? 17:05 How to interpret R and R2 in a Multiple Linear Regression? 20:27 What are Dummy Variables? 25:39 What is a Logistic Regression?Mann–Whitney U testnumiqo2025-01-07 | The Mann–Whitney U test (also known as the Wilcoxon rank-sum test) is a non-parametric statistical test used to compare two independent groups to determine whether their population distributions differ. It is often used as an alternative to the independent samples t-test when the assumption of normality in the data cannot be satisfied.
#Statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationSpearmans rank correlation coefficientnumiqo2025-01-06 | The Spearman's rank correlation coefficient is a non-parametric measure of the strength and direction of the association between two ranked variables. It assesses how well the relationship between two variables can.
#Statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationPearson correlation coefficient #Statistics #DataScience #DataAnalysisnumiqo2025-01-04 | Pearson Correlation Coefficient! 📊 Discover how this powerful metric measures the strength and direction of linear relationships between two variables. Perfect for students, data enthusiasts, and anyone diving into analytics. Learn when to use it, how to calculate it, and what those results really mean! 💡
#PearsonCorrelation #Statistics #DataScience #CorrelationCoefficient #MathExplained #LinearRelationship #DataAnalysis #LearnStatistics #MathTutorial #DataVisualizationSimple Linear Regression: An Easy and Clear Beginner’s Guidenumiqo2024-12-08 | In this video, you’ll learn the basics of Simple Linear Regression: what it is, how it works, and why it’s useful. We’ll walk through the key concepts, show you how to calculate the regression equation step by step, and discuss the main assumptions you need to check for a valid model.
00:00 What is a Simple Linear Regression? 00:53 Example for a Simple Linear Regression. 1:36 How to calculate a Simple Linear Regression? 3:04 What is the slope and the intercept? 7:05 How to calculate a Simple Linear Regression with DATAtab? 8:01 How do you interpret the p-value? 9:23 What are the assumptions of a Simple Linear Regression? 13:32 Multiple Linear RegressionRegression Analysis: An Easy and Clear Beginner’s Guidenumiqo2024-11-26 | In this video on Regression Analysis, we’ll cover Simple Linear Regression, Multiple Linear Regression, and Logistic Regression.
Logistic Regression numiqo.com/tutorial/logistic-regressionMastering Odds Ratios in Logistic Regression – A Step-by-Step Guidenumiqo2024-11-11 | This Video is about odds ratios in logistic regression. If you’ve ever wondered how to interpret odds ratios, why they’re so crucial in logistic regression, or just want a better understanding of what they actually mean, this video is for you! We’ll start with a quick overview of logistic regression, then dive into what odds are and how they work. From there, we'll break down the odds ratio, and finally, we’ll bring it all together to see what the odds ratio means within the context of logistic regression.
00:00 Odds Ratios in Logistic Regression 00:31 What is a Logistic Regression? 01:52 What are Odds? 03:14 What are Odds Ratios? 06:04 How to interpret Odds Ratios in a Logistic Regression?The New Statistics: A Modern Approach to Data Analysisnumiqo2024-10-24 | Is there a new way to do statistics? Yes, there is! In this video, we'll dive into modern solutions to tackle the challenges of traditional methods. Specifically, we'll focus on practical alternatives to overcome the 'p-value dilemma,' a topic we explored in our previous video, Is the p-value dead? We will focus on the book “New Statistics” by Geoff Cumming and Robert Calin-Jageman.
0:00 What is the New Statistics Approach? 2:00 What are the 3 main problems of empirical research? 7:24 What are the 4 solutions? 14:58 Example and ConclusionLearn Correlation Analysis Fast – 90% of What You Need in Under 11 Minutesnumiqo2024-10-14 | In this video, we dive into the concept of correlation – a powerful statistical tool used to measure the relationship between two variables. Whether you’re analyzing data for school, work, or just curious about how trends are connected, this video explains everything you need to know!
► E-BOOK numiqo.com/statistics-bookANOVA - A Full Lecture to learn Analysis of Variancenumiqo2024-10-08 | Welcome to this full and free course on analysis of variance, or ANOVA for short. In this video, we'll explore what analysis of variance actually is and why you need it. We’ll take a deep dive into the different types of ANOVA, helping you understand when and how to use each one. We'll start with the basics of the One-Way ANOVA, then move on to the more advanced Two-Way ANOVA, ANOVA with repeated measures, and the powerful Mixed Model ANOVA.
0:00 Introduction 1:10 One-Way ANOVA 14:25 Two-Way ANOVA 30:46 ANOVA with repeated measures 45:06 Mixed Model ANOVAConfidence Interval: The right and wrong way to understand them.numiqo2024-10-02 | In this video, we'll uncover the true definition of a confidence interval, clear up some common misconceptions, and explain the difference between the incorrect and correct interpretations. In fact, published studies have shown that professional scientists frequently misinterpret confidence intervals.
► Statistics Calculator numiqo.com/statistics-calculator/descriptive-statisticsTypes of Data in Statistics - Nominal, Ordinal, Interval, and Rationumiqo2024-09-30 | This video is about types of data in statistics. In statistics, "types of data" are generally referred to as "levels of measurement". We're going to explore the four levels of measurement —Nominal, Ordinal, Interval, and Ratio. Each level gives us important information about the variable and supports different types of statistical analysis.
0:00 What are types of data in statistics? 2:58 What are nominal variables? 4:20 What are ordinal variables? 5:21 What are metric variables? 5:59 Example of nominal, ordinal and metric data. 8:08 What is the difference between interval and ratio data 10:37 Exercise on Levels of MeasurementOne-Way-ANOVA #maths #pvalue #statistics #datascience #dataanalysis #research #thesis #statsnumiqo2024-09-25 | This video is about analysis of variance, or ANOVA for short.One-Way ANOVA [Analysis of Variance] simply explainednumiqo2024-09-25 | This video is about analysis of variance, or ANOVA for short. We discuss what an ANOVA is and why you need it. We look at the hypotheses and the prerequisites for an analysis of variance, and I show you how to calculate an ANOVA and what the equations behind an ANOVA are. Finally, we discuss how to interpret the results and take a look at the post-hoc test. First of all, there are different types of analysis of variance. The simplest and most common form is the one-way analysis of variance. And this video is all about the one-way analysis of variance.
00:00 What is an analysis of variance? 01:53 What are the hypotheses in an analysis of variance? 02:29 What are the assumptions of an analysis of variance? 05:55 How is an ANOVA calculated? 12:16 How is an analysis of variance calculated with DATAtab? 13:00 What is a post-hoc test?80% of Regression Analysis Basics in under 18 Minutes [Simple, Multiple and Logistic Regression]numiqo2024-09-08 | But have you ever wondered why your data keeps crossing the line? Today we’re diving into simple linear, multiple linear, and logistic regression, and it will be entertaining- I promise!
0:00 Intro 0:27 Simple linear Regression 6:40 Multiple linear Regression 11:57 Logistic Regression 14:57 Examples of Regression AnalysisWhen not to use the t-test! 3 Scenarios Where the T-Test Fails...numiqo2024-08-20 | Are you relying on the t-test in every situation? It might be time to rethink that approach! In this video, we dive into three specific cases where the t-test can lead you astray, and explain why alternative methods are better suited for these scenarios. Whether you're in research, data analysis, or just curious about statistical techniques, understanding when not to use the t-test is crucial.
0:00 Intro 0:18 What is a t-Test? 4:05 When not to use the t-testControl Charts simply explained - Statistical process control - Xbar-R Chart, I-MR Chart,...numiqo2024-08-13 | In this video, we delve into the fundamentals of Control Charts (Statistical Process Control - SPC), a vital tool in quality control and process management. Learn how to monitor processes, detect variations, and maintain consistent quality over time.
We'll cover: What Control Charts are and why they are essential. Different types of Control Charts (Xbar-R Chart, I-MR Chart, p Chart, np Chart, c Chart and u Chart). How to create and interpret Control Charts. Real-world examples of using Control Charts in various industries.
0:00 What are Control Charts? 1:04 What is a Xbar-R Chart? 5:05 What is an I-MR Chart? 6:34 What is a np Chart and a p Chart? 9:08 What is a c Chart and a u Chart?Why the p-Value fell from Grace: A Deep Dive into Statistical Significancenumiqo2024-08-04 | In this video, we dive deep into the contentious world of the p-Value, a fundamental concept in statistical analysis. 📊
The p-Value has been a critical tool for researchers across various fields, helping them determine the significance of their results. However, it has also been the subject of intense debate and scrutiny. In this video, we break down the pros and cons of using the p-Value in scientific research.
We'll cover: ✅ The benefits and strengths of the p-Value in hypothesis testing and data analysis. ⚠️ Common pitfalls and criticisms associated with the p-Value. 🔍 Examples where the p-Value has been both useful and misleading. 🔄 Alternative methods and metrics to consider for statistical significance. 🤔 How to use the p-Value correctly and avoid common mistakes.
Whether you're a student, a researcher, or just someone interested in the intricacies of data analysis, this video will provide a balanced perspective on the p-Value, highlighting its advantages and limitations.
Join us as we explore the practical applications and the controversies surrounding the p-Value, helping you make more informed decisions in your research and data analysis endeavors.
Sources: - Lakens, D. (2021): The Practical Alternative to the p Value Is the Correctly Used p Value. Perspectives on Psychological Science, 16(3), 639-648. - Trafimow , D.& Marks, M. ( 2015 ): Editorial . Basic and Applied Social Psychology , 37(1), 1-2 . - Lu, Ying & Belitskaya-Levy (2015): The debate about p-values. Shanghai Archives of Psychiatry. 27(6): 381–385. - Hirschauer, Norbert (2022): Unanswered Questions in the p-value debate. Significance, 19(3), 42-44.
#Statistics #pValue #DataAnalysis #ResearchMethods #HypothesisTestingStatistics - A Full Lecture to learn Data Sciencenumiqo2024-05-02 | Welcome to our full and free tutorial about statistics (Full-Lecture). We will uncover the tools and techniques that help us make sense of data. This video is designed to guide you through the fundamental concepts and some of the most powerful statistical tests used in research today. From the basics of descriptive statistics to the complexities of regression and beyond, we'll explore how each method fits into the bigger picture of data analysis.
0:00 Intro 1:25 Basics of Statistics 21:29 Level of Measurement 34:26 t-Test 50:53 ANOVA (Analysis of Variance) 59:55 Two-Way ANOVA 1:16:47 Repeated Measures ANOVA 1:31:15 Mixed-Model ANOVA 1:42:56 Parametric and non parametric tests 1:50:37 Test for normality 1:58:41 Levene's test for equality of variances 2:02:54 Non-parametric Tests 2:03:29 Mann-Whitney U-Test 2:11:46 Wilcoxon signed-rank test 2:22:03 Kruskal-Wallis-Test 2:32:01 Friedman Test 2:42:30 Chi-Square test 2:53:02 Correlation Analysis 3:20:19 Regression Analysis 4:06:45 k-means clusteringLevels of Measurement - Nominal, Ordinal, Interval and Rationumiqo2024-04-25 | In this video, we're going to explore the four levels of measurement —Nominal, Ordinal, Interval, and Ratio. Each level gives us important information about the variable and supports different types of statistical analysis.
0:00 What are Levels of Measurement? 2:37 What are nominal variables? 3:59 What are ordinal variables? 5:00 What are metric variables? 5:38 Example of nominal, ordinal and metric data. 7:47 What is the difference between interval and ratio data 10:16 Exercise on Levels of MeasurementRepeated Measures ANOVA (Analysis of Variance) - Simply explainednumiqo2024-04-17 | This video is about repeated measures ANOVA (Analysis of Variance), we go through the following questions: What is repeated measures analysis of variance? What are the hypotheses and assumptions? How is an analysis of variance with repeated measures calculated? How are the results interpreted? What is a post hoc test and how do I interpret it correctly? An analysis of variance with repeated measures tests whether there is a statistically significant difference between three or more dependent samples.
0:00 What is a repeated measures analysis of variance (ANOVA with repeated measures)? 3:05 What are the hypotheses? 4:06 What are the assumptions? 5:11 How is an analysis of variance with repeated measures calculated and interpreted? 9:06 What are the formulas for calculating repeated measures ANOVA by hand?z-Score, z-Standardization, Standard Normal Distribution, z-Distribution Table - Simply explainednumiqo2024-03-19 | In this video, we discuss what the z-Score is, how z-standardisation (z-transformation) works and what the standard normal distribution is. I will also show you what the z-distribution table (standard normal distribution table) is and what you need it for. For a better understanding, let's go through the individual points using a simple example.
0:00 What is the z-Score? 3:23 What is z-standardisation (z-transformation)? 5:38 What is the standard normal distribution? 6:39 What is the z-distribution table (standard normal distribution table)? 9:28 Example of z-standardisation (z-transformation) 10:17 z-Standardisation: Make values measured in different ways comparable. 11:57 What are the assumptions for z-standardisation and the z-distribution table?What is the difference between parametric and nonparametric hypothesis testing?numiqo2024-03-10 | Hi, in this video I explain the difference between parametric and non-parametric tests! You want to calculate a hypothesis test, but don't know exactly what the difference is between a parametric and non-parametric test and are wondering when to use which test. If you want to calculate a hypothesis test, you must first check the assumptions for the respective hypothesis test. One of the most common assumption is that the data used must be normally distributed. Put simply, if your data is normally distributed, parametric tests are used, e.g. the t-test, analysis of variance or pearson correlation. If your data is not normally distributed, non-parametric tests are used, e.g. the Mann-Whitney U test or the Spearman correlation.
0:00 What are parametric and non-parametric hypothesis tests? 1:54 Pearson correlation vs. the Spearman correlation 4:00 t-test for independent samples vs. Mann Whitney U test 5:43 List of parametric and non-parametric hypothesis tests. 6:17 Calculating parametric and non-parametric hypothesis tests with DATAtabWhat is Descriptive Statistics? A Beginners Guide to Descriptive Statistics!numiqo2024-03-05 | Descriptive statistics is a branch of statistics that involves summarizing and organizing data in a way that it can be easily understood. This statistical method focuses on describing and understanding the features of a specific data set by providing summaries about the sample and measures of the data. The main goal is to present a large amount of data in a clear and concise manner for easy interpretation, without making any conclusions beyond the data itself or inferring any patterns that may apply to a larger population.
0:00 What is Descriptive Statistics? 1:05 What are Measures of Central Tendency? 2:51 What are Measures of Dispersion? 6:06 What are Frequency table and Contingency table? 8:07 Charts in Descriptive StatisticsWhat is a hypothesis test? A beginners guide to hypothesis testing!numiqo2024-02-26 | Hypothesis testing is used to determine whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population. Therefore, it's a method to test an assumption or theory about a parameter of a population based on a sample.
► Tutorial numiqo.com/tutorial/hypothesis-testingWhat is Statistics? A Beginners Guide to Statistics (Data Analytics)!numiqo2024-02-18 | If you want to finally understand statistics, this is the place to be! After this video, you will know what statistics is, what descriptive statistics is and what inferential statistics is. Statistics is the science of collecting, analyzing, interpreting, and presenting data. Statistics is integral to various fields, including business, economics, engineering, medicine, social sciences, and natural sciences, among others. It encompasses a wide range of techniques and processes for dealing with data, including:
Descriptive Statistics: This branch focuses on summarizing and describing the features of a dataset through measures such as mean, median, mode, and standard deviation, as well as through graphs and charts. It aims to provide a clear overview of the data without making inferences about a larger population.
Inferential Statistics: This branch uses samples of data to make generalizations or predictions about a larger population. It includes hypothesis testing, confidence intervals, regression analysis, and analysis of variance. Inferential statistics allows researchers to draw conclusions beyond the immediate data, estimating population parameters and testing hypotheses.
0:00 What is Statistics? 2:24 What is Descriptive Statistics? 12:12 What is Inferential Statistics?Fractional Factorial Design (DoE) Simply explainednumiqo2024-02-07 | What is a Fractional Factorial Design? A fractional factorial design is a type of experimental design used to analyse the effects of several factors (or variables) on a response variable. What is the difference with a full factorial design? In a full factorial design, every possible combination of factor levels is examined. Conversely, a fractional factorial design strategically excludes certain combinations. This reduce the number of experiments while still capturing essential information about the system's behavior.
► Fractional Factorial Design Tutorial numiqo.com/tutorial/fractional-factorial-designBetween-Subject Design vs. Within-Subject Designnumiqo2024-02-05 | What is the difference between a Between-subject Design and a Within-subject Design? And why is it important to know the difference? This is what we discuss in this video!
0:00 What is a Mixed Model ANOVA? 3:50 What are the hypotheses in a Mixed Model ANOVA? 4:45 What are the assumptions in a Mixed Model ANOVA? 6:40 Example of a Mixed Model ANOVA. 7:26 How to calculate and interpret a Mixed Model ANOVA?Full Factorial Design (DoE - Design of Experiments) Simply explainednumiqo2024-01-25 | In this video, we discuss what a full factorial design is, how to create it and how to analyze the results obtained. A full factorial design is a systematic method for examining the effects and possible interactions of multiple factors on a response variable.
0:00 What is a full factorial design? 2:24 How can the number of runs needed be estimated? 5:38 How can a full factorial design help to reduce the number of runs? 9:06 Creating a full factorial design online. 10:51 Analyse and interpret a full factorial design.Design of Experiments (DoE) simply explainednumiqo2024-01-22 | In this video, we discuss what Design of Experiments (DoE) is. We go through the most important process steps in a DoE project and discuss how a DoE helps you to reduce the number of experiments. We then discuss how you can estimate the number of experiments needed and we go through the most common experimental designs: Full factorial design, Fractional factorial design, Plackett-Burman Design, Box-Behnken Design, Central Composite Design.
0:00 What is design of experiments? 3:12 Steps of DOE project 5:56 Types of Designs 6:26 Why design of experiments and why do you need statistics? 6:47 How are the number of experiments in a DoE estimated? 9:26 How can DoE reduce the number of runs? 10:09 What is a full factorial design? 12:04 What is a fractional factorial design? 15:27 What is the resolution of a fractional factorial design? 21:54 What is a Plackett-Burman design? 22:46 What is a Box-Behnken design? 24:00 What is a Central Composite Design? 24:34 Creating a DoE onlineWhat is inferential statistics? Explained in 6 simple Steps.numiqo2023-11-22 | In this video we are gone talk about what inferential statistics does in 6 simple steps (Hypothesis, Population and Sample, Hypothesis Testing, p-Value, Statistical Significance, Errors). But, what is inferential statistics? Inferential statistics allows us to make conclusions or inferences about a population based on data from a sample.
0:00 What is inferential statistics? 0:26 What is a sample and a population? 1:00 What is a Hypothesis? 1:41 What is Hypothesis Testing? 3:50 What is statistics significance? 4:50 What is a Type I and type II error? 6:30 How do I find a suitable hypothesis test?