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Basic Statistics

Курс от University of Amsterdam
Начальный≈ 17.4 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression. The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work. The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests. Normally, you would not only learn about all these statistical concepts, but you would also be trained to calculate and generate these statistics yourself using freely available statistical software. Due to technical issues we are currently unable to do so. We will try to offer this again soon.

Навыки, которые вы освоите

Statistical Hypothesis TestingQuantitative ResearchData Analysis SoftwareStatistical MethodsProbability & StatisticsStatistical AnalysisStatistics

Программа курса

9 модулей · 110 учебных материалов

01Before we get started...13 материалов

Course introduction

Hi there!ЧтениеWelcome to Basic Statistics!ВидеоHow to navigate this courseЧтениеHow to contributeЧтение

What to expect from this course

Учитесь у экспертов

Matthijs Rooduijn

Dr.

Emiel van Loon

Assistant Professor

Basic Statistics
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 17.4 ч

9 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
General info - What will I learn in this course?Чтение
Course format - How is this course structured?Чтение
Requirements - What resources do I need?Чтение
Grading - How do I pass this course?Чтение
Team - Who created this course?Чтение
Honor Code - Integrity in this courseЧтение
Useful literature and documentsЧтение
Research on FeedbackЧтение
Use of your data for researchЗадание
02Exploring Data13 материалов

Data and visualisation

Data and visualisationЧтение1.01 Cases, variables and levels of measurementВидео1.02 Data matrix and frequency tableВидео1.03 Graphs and shapes of distributionsВидео

Measures of central tendency and dispersion

Measures of central tendency and dispersionЧтение1.04 Mode, median and meanВидео1.05 Range, interquartile range and box plotВидео1.06 Variance and standard deviationВидео

Z-scores and example

Z-scores and exampleЧтение1.07 Z-scoresВидео1.08 ExampleВидео

Review

Transcripts - Exploring dataЧтениеExploring DataЗадание
03Correlation and Regression15 материалов

Correlation

CorrelationЧтение2.01 Crosstabs and scatterplotsВидео2.02 Pearson's rВидео

Regression

RegressionЧтение2.03 Regression - Finding the lineВидео2.04 Regression - Describing the lineВидео2.05 Regression - How good is the line?ВидеоReferenceЧтение

Caveats & examples

Caveats and examplesЧтение2.06 Correlation is not causationВидео2.07 Example contingency tableВидео2.08 Example Pearson's r and regressionВидеоReferenceЧтение

Review

Transcripts - Correlation and regressionЧтениеCorrelation and RegressionЗадание
04Probability17 материалов

Probability & Randomness

Probability & randomnessЧтение3.01 RandomnessВидео3.02 ProbabilityВидео

Sample space, events & tree diagrams

Sample space, events & tree diagramsЧтение3.03 Sample space, event, probability of event and tree diagramВидео3.04 Quantifying probabilities with tree diagramВидео

Probability & sets

Probability & setsЧтение3.05 Basic set-theoretic conceptsВидео3.06 Practice with setsВидео3.07 UnionВидео

Conditional probability & Independence

Conditional probability & independenceЧтение3.08 Joint and marginal probabilitiesВидео3.09 Conditional probabilityВидео3.10 Independence between random eventsВидео3.11 More conditional probability, decision trees and Bayes' LawВидео

Review

Transcripts - ProbabilityЧтениеProbabilityЗадание
05Probability Distributions14 материалов

Probability distributions

Probability distributionsЧтение4.01 Random variables and probability distributionsВидео4.02 Cumulative probability distributionsВидео

Mean and variance of a random variable

Mean and variance of a random variableЧтение4.03 The mean of a random variableВидео4.04 Variance of a random variableВидео

The normal distribution

The normal distributionЧтение4.05 Functional form of the normal distributionВидео4.06 The normal distribution: probability calculationsВидео4.07 The standard normal distributionВидео

The binomial distribution

The binomial distributionЧтение4.08 The binomial distributionВидео

Review

Transcripts - Probability distributionsЧтениеProbability distributionsЗадание
06Sampling Distributions13 материалов

Sample and sampling

Sample and samplingЧтение5.01 Sample and populationВидео5.02 SamplingВидео

Sampling distribution of sample mean and central limit theorem

Sampling distribution of sample mean and central limit theoremЧтение5.03 The sampling distributionВидео5.04 The central limit theoremВидео5.05 Three distributionsВидеоReferenceЧтение

Sampling distribution of sample proportion and example

Sampling distribution of sample proportion and exampleЧтение5.06 Sampling distribution proportionВидео5.07 ExampleВидео

Review

Transcripts - Sampling distributionsЧтениеSampling distributionsЗадание
07Confidence Intervals12 материалов

Inference and confidence interval for mean

Inference and confidence interval for meanЧтение6.01 Statistical inferenceВидео6.02 CI for mean with known population sdВидео6.03 CI for mean with unknown population sdВидео

Confidence interval for proportion and confidence levels

Confidence interval for proportion and confidence levelsЧтение6.04 CI for proportionВидео6.05 Confidence levelsВидео

Sample size and example

Sample size and exampleЧтение6.06 Choosing the sample sizeВидео6.07 ExampleВидео

Review

Transcripts - Confidence intervalsЧтениеConfidence intervalsЗадание
08Significance Tests12 материалов

Hypotheses and significance tests

Hypotheses and significance testsЧтение7.01 HypothesesВидео7.02 Test about proportionВидео7.03 Test about meanВидео

Step-by-step plan and confidence interval

Step-by-step plan and confidence intervalЧтение7.04 Step-by-step planВидео7.05 Significance test and confidence intervalВидео

Type I and Type II errors and example

Type I and Type II errors and exampleЧтение7.06 Type I and Type II errorsВидео7.07 ExampleВидео

Review

Transcripts - Significance testsЧтениеSignificance testsЗадание
09Exam time!1 материалов

Final exam

Final ExamЗадание