Nederlands
Courses
Nederlands
sowiso logo General Statistics

Open course on descriptive and inferential statistics with theory and interactive exercises.
Offered by the Teaching and Learning Centre of FNWI

Full access via UvAnetID

Available languages: 
en
Course content
0. The Basics of R
Starting-up
THEORY
T
1.
Introduction
THEORY
T
2.
Setting-up online access
THEORY
T
3.
Download and Install for off-line use
THEORY
T
4.
Finding your way in RStudio
THEORY
T
5.
Getting Help
Using R
THEORY
T
1.
Making calculations
THEORY
T
2.
Working with vectors
THEORY
T
3.
Working with data frames
Practical 0
THEORY
T
1.
Introducing the gapminder data set
THEORY
T
2.
Exploring the data
THEORY
T
3.
Selecting subsets
PRACTICE
P
4.
Exploring the gapminder data
9
1. Descriptive Statistics
Types of Data and Measurement
THEORY
T
1.
Qualitative and Quantitative Variables
PRACTICE
P
2.
Qualitative and Quantitative Variables
9
THEORY
T
3.
The Hierarchy of Measurement Scales
PRACTICE
P
4.
The Hierarchy of Measurement Scales
2
THEORY
T
5.
Nominal Scale
PRACTICE
P
6.
Nominal Scale
5
THEORY
T
7.
Ordinal Scale
PRACTICE
P
8.
Ordinal Scale
5
THEORY
T
9.
Interval Scale
PRACTICE
P
10.
Interval Scale
5
THEORY
T
11.
Ratio Scale
PRACTICE
P
12.
Ratio Scale
5
Frequency Distributions
THEORY
T
1.
Frequency Distributions
THEORY
T
2.
Frequency Distribution Tables
PRACTICE
P
3.
Frequency Distribution Tables
3
THEORY
T
4.
Frequency Distribution Graphs
PRACTICE
P
5.
Frequency Distribution Graphs
7
THEORY
T
6.
Shape of a Distribution
PRACTICE
P
7.
Shape of a Distribution
8
THEORY
T
8.
Measures of Location I: Quantiles
PRACTICE
P
9.
Measures of Location I: Quantiles
6
Measures of Central Tendency
THEORY
T
1.
Introduction to Central Tendency
THEORY
T
2.
Mode
PRACTICE
P
3.
Mode
6
THEORY
T
4.
Median
PRACTICE
P
5.
Median
6
THEORY
T
6.
Mean
PRACTICE
P
7.
Mean
9
THEORY
T
8.
Central Tendency and the Shape of a Distribution
PRACTICE
P
9.
Central Tendency and the Shape of a Distribution
2
THEORY
T
10.
Sensitivity to Outliers
PRACTICE
P
11.
Sensitivity to Outliers
1
Measures of Variability
THEORY
T
1.
Range, Interquartile Range, and the Five-Number Summary
PRACTICE
P
2.
Range, Interquartile Range, and the Five-Number Summary
5
THEORY
T
3.
Interquartile Range Rule for Identifying Outliers
PRACTICE
P
4.
Interquartile Range Rule for Identifying Outliers
2
THEORY
T
5.
Deviation from the Mean and the Sum of Squares
PRACTICE
P
6.
Deviation from the Mean and the Sum of Squares
5
THEORY
T
7.
Variance and Standard Deviation
PRACTICE
P
8.
Variance and Standard Deviation
6
Measures of Location II: Z-scores
THEORY
T
1.
Z-scores
PRACTICE
P
2.
Z-scores
14
Practical 1
THEORY
T
1.
Introduction
THEORY
T
2.
Measures of Central Tendency
PRACTICE
P
3.
Measures of Central Tendency
6
THEORY
T
4.
Measures of Spread
PRACTICE
P
5.
Measures of Spread
2
THEORY
T
6.
Keypoints
2. Association and Correlation
Correlation
THEORY
T
1.
Introduction to Correlation
THEORY
T
2.
Displaying the Relationship Between Two Variables
PRACTICE
P
3.
Displaying the Relationship Between Two Variables
3
THEORY
T
4.
Measuring the Relationship Between Two Variables
PRACTICE
P
5.
Measuring the Relationship Between Two Variables
7
THEORY
T
6.
Direction of a Linear Relationship: Covariance
PRACTICE
P
7.
Direction of a Linear Relationship: Covariance
2
THEORY
T
8.
Strength of a Linear Relationship: Pearson Correlation Coefficient
PRACTICE
P
9.
Strength of a Linear Relationship: Pearson Correlation Coefficient
3
THEORY
T
10.
Monotonic Relationship: Spearman Correlation Coefficient
PRACTICE
P
11.
Monotonic Relationship: Spearman Correlation Coefficient
3
Practical 2
THEORY
T
1.
Introduction
PRACTICE
P
2.
Data Exploration
5
THEORY
T
3.
Visualising the Relationship Between Two Variables
PRACTICE
P
4.
Visualising the Relationship Between Two Variables
1
THEORY
T
5.
Pearson Correlcation Coefficient
PRACTICE
P
6.
Pearson Correlation Coefficient
9
THEORY
T
7.
Spearman Correlation Coefficient
PRACTICE
P
8.
Spearman Correlation Coefficient
6
3. Probability
Randomness
THEORY
T
1.
Sets, Subsets and Elements
PRACTICE
P
2.
Sets, Subsets and Elements
3
THEORY
T
3.
Random Experiments
THEORY
T
4.
Sample Space
PRACTICE
P
5.
Sample Space
5
THEORY
T
6.
Events
PRACTICE
P
7.
Events
2
THEORY
T
8.
Complement of an Event
PRACTICE
P
9.
Complement of an Event
2
Relationship between Events
THEORY
T
1.
Mutual Exclusivity
PRACTICE
P
2.
Mutual Exclusivity
2
THEORY
T
3.
Difference
PRACTICE
P
4.
Difference
8
THEORY
T
5.
Intersection
PRACTICE
P
6.
Intersection
5
THEORY
T
7.
Union
PRACTICE
P
8.
Union
1
Probability
THEORY
T
1.
Definition of Probability
PRACTICE
P
2.
Definition of Probability
5
THEORY
T
3.
Probability of the Complement
PRACTICE
P
4.
Probability of the Complement
4
THEORY
T
5.
Conditional Probability
PRACTICE
P
6.
Conditional Probability
2
THEORY
T
7.
Independence
PRACTICE
P
8.
Independence
4
THEORY
T
9.
Probability of the Intersection
PRACTICE
P
10.
Probability of the Intersection
2
THEORY
T
11.
Probability of the Union
PRACTICE
P
12.
Probability of the Union
5
THEORY
T
13.
Probability of the Difference
PRACTICE
P
14.
Probability of the Difference
2
THEORY
T
15.
Law of Total Probability
PRACTICE
P
16.
Law of Total Probability
1
THEORY
T
17.
Bayes' Theorem
PRACTICE
P
18.
Bayes' Theorem
3
Contingency Tables
THEORY
T
1.
Interpreting Contingency Tables
PRACTICE
P
2.
Interpreting Contingency Tables
7
Practical 3
THEORY
T
1.
Introduction
PRACTICE
P
2.
Data Exploration
3
THEORY
T
3.
Contingency Tables
PRACTICE
P
4.
Calculate Probabilities
7
THEORY
T
5.
Extention on Contingency Tables
PRACTICE
P
6.
Contingency Tables With 3 Variables
2
THEORY
T
7.
Probability Rules
PRACTICE
P
8.
Probability Rules
7
THEORY
T
9.
Keypoints
4. Probability Distributions
Probability Models
THEORY
T
1.
Discrete Probability Models
PRACTICE
P
2.
Discrete Probability Models
2
THEORY
T
3.
Continuous Probability Models
PRACTICE
P
4.
Continuous Probability Models
2
Random Variables
THEORY
T
1.
Random Variables
PRACTICE
P
2.
Random Variables
6
THEORY
T
3.
Probability Distributions
PRACTICE
P
4.
Probability Distributions
2
THEORY
T
5.
Expected Value of a Random Variable
PRACTICE
P
6.
Expected Value of a Random Variable
3
THEORY
T
7.
Variance of a Random Variable
PRACTICE
P
8.
Variance of a Random Variable
5
THEORY
T
9.
Sums of Random Variables
PRACTICE
P
10.
Sums of Random Variables
6
Common Distributions
THEORY
T
1.
The Binomial Distribution
PRACTICE
P
2.
The Binomial Distribution
14
THEORY
T
3.
Expected Value and Variance of a Binomial Random Variable
PRACTICE
P
4.
Expected Value and Variance of a Binomial Random Variable
3
THEORY
T
5.
The Normal Distribution
PRACTICE
P
6.
The Normal Distribution
6
THEORY
T
7.
The Normal Probability Distribution
PRACTICE
P
8.
The Normal Probability Distribution
13
Practical 4
THEORY
T
1.
Introduction
THEORY
T
2.
Normal random variables
PRACTICE
P
3.
The Normal Distribution
13
THEORY
T
4.
Binomial random variables
PRACTICE
P
5.
The Binomial Distribution
4
THEORY
T
6.
Random variables
PRACTICE
P
7.
Random variables
2
THEORY
T
8.
Combinations of random variables
PRACTICE
P
9.
Combinations of random variables
3
THEORY
T
10.
Keypoints
5. Sampling
Sampling and Sampling Methods
THEORY
T
1.
Sampling and Unbiased Sampling Methods
PRACTICE
P
2.
Sampling and Unbiased Sampling Methods
2
THEORY
T
3.
Biased Sampling Methods
PRACTICE
P
4.
Sampling Methods
6
Sampling Distributions
THEORY
T
1.
Sampling Distributions
PRACTICE
P
2.
Sampling Distributions
3
THEORY
T
3.
Sampling Distribution of the Sample Mean
PRACTICE
P
4.
Sampling Distribution of the Sample Mean
17
THEORY
T
5.
Sampling Distribution of the Sample Proportion
PRACTICE
P
6.
Sampling Distribution of the Sample Proportion
8
Practical 5a
THEORY
T
1.
Introduction
PRACTICE
P
2.
Data Exploration
6
THEORY
T
3.
Simple Random Sampling
PRACTICE
P
4.
Simple Random Sampling
2
THEORY
T
5.
Stratified Sampling
PRACTICE
P
6.
Stratified Sampling
4
THEORY
T
7.
Cluster Sampling
PRACTICE
P
8.
Cluster Sampling
3
THEORY
T
9.
Keypoints
Practical 5b
THEORY
T
1.
Introduction
PRACTICE
P
2.
Data Exploration
2
THEORY
T
3.
Construct the Sampling Distribution of any Statistic
PRACTICE
P
4.
Sampling Distribution
4
THEORY
T
5.
Central Limit Theorem
THEORY
T
6.
Keypoints
6. Parameter Estimation and Confidence Intervals
Estimation
THEORY
T
1.
Parameter Estimation
PRACTICE
P
2.
Parameter Estimation
3
THEORY
T
3.
Constructing a 95% Confidence Interval for the Population Mean
PRACTICE
P
4.
Constructing a 95% Confidence Interval for the Population Mean
5
THEORY
T
5.
Confidence Interval for the Population Mean
PRACTICE
P
6.
Confidence Interval for the Population Mean
13
THEORY
T
7.
Confidence Interval for the Population Proportion
PRACTICE
P
8.
Confidence Interval for the Population Proportion
10
Practical 6
THEORY
T
1.
Introduction
THEORY
T
2.
Recap: Sample Versus Population
THEORY
T
3.
Sample Mean and Confidence Interval
PRACTICE
P
4.
Confidence Interval
5
THEORY
T
5.
Multiple Samples
PRACTICE
P
6.
Multiple samples
2
THEORY
T
7.
Varying the Confidence Level
PRACTICE
P
8.
Varying the Confidence Level
3
THEORY
T
9.
Confidence Intervals for Proportions
PRACTICE
P
10.
Confidence intervals for proportions
3
THEORY
T
11.
Keypoints
7. Hypothesis Testing
Introduction to Hypothesis Testing
THEORY
T
1.
Hypothesis Testing Procedure
PRACTICE
P
2.
Hypothesis Testing Procedure
1
THEORY
T
3.
Formulating the Research Hypotheses
PRACTICE
P
4.
Formulating the Research Hypotheses
4
THEORY
T
5.
Two-tailed vs. One-tailed Testing
PRACTICE
P
6.
Two-tailed vs. One-tailed Testing
7
THEORY
T
7.
Setting the Criteria for a Decision
PRACTICE
P
8.
Setting the Criteria for a Decision
2
THEORY
T
9.
Computing the Test Statistic and Making a Decision
PRACTICE
P
10.
Computing the Test Statistic and Making a Decision
4
THEORY
T
11.
Computing the p-value and Making a Decision
PRACTICE
P
12.
Computing the p-value and Making a Decision
12
THEORY
T
13.
Assumptions of the z-test
PRACTICE
P
14.
Assumptions of the z-test
1
THEORY
T
15.
Connection Between Hypothesis Testing and Confidence Intervals
PRACTICE
P
16.
Connection Between Hypothesis Testing and Confidence Intervals
5
THEORY
T
17.
Errors in Decision Making
PRACTICE
P
18.
Errors in Decision Making
5
THEORY
T
19.
Statistical Power
PRACTICE
P
20.
Statistical Power
9
Hypothesis Test for a Population Proportion
THEORY
T
1.
Hypotheses of a Population Proportion Test
PRACTICE
P
2.
Hypotheses of a Population Proportion Test
4
THEORY
T
3.
Large-sample Proportion Test: Test Statistic and p-value
PRACTICE
P
4.
Large-sample Proportion Test: Test Statistic and p-value
6
THEORY
T
5.
Small-sample Proportion Test: Test Statistic and p-value
PRACTICE
P
6.
Small-sample Proportion Test: Test Statistic and p-value
6
THEORY
T
7.
Hypothesis Test for a Proportion and Confidence Intervals
PRACTICE
P
8.
Hypothesis Test for a Proportion and Confidence Intervals
4
One-sample t-test
THEORY
T
1.
One-sample t-test: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
One-sample t-test: Purpose, Hypotheses, and Assumptions
5
THEORY
T
3.
One-sample t-test: Test Statistic and p-value
PRACTICE
P
4.
One-sample t-test: Test Statistic and p-value
6
THEORY
T
5.
Confidence Interval for μ when σ is Unknown
PRACTICE
P
6.
Confidence Interval for μ when σ is Unknown
6
Practical 7
THEORY
T
1.
Introduction to Hypothesis Testing
PRACTICE
P
2.
Introduction to Hypothesis Testing
3
THEORY
T
3.
Introduction to Air Quality Case Study
PRACTICE
P
4.
Data Exploration
4
THEORY
T
5.
One-sample t-test
PRACTICE
P
6.
Hypothesis Testing on Means
3
THEORY
T
7.
Testing for Differences Between Proportions
PRACTICE
P
8.
Hypothesis Testing on Proportions
3
THEORY
T
9.
Keypoints
8. Testing for Differences in Means and Proportions
Paired Samples t-test
THEORY
T
1.
Paired Samples t-test: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
Paired Samples t-test: Purpose, Hypotheses, and Assumptions
4
THEORY
T
3.
Paired Samples t-test: Test Statistic and p-value
PRACTICE
P
4.
Paired Samples t-test: Test Statistic and p-value
9
THEORY
T
5.
Confidence Interval for a Mean Difference
PRACTICE
P
6.
Confidence Interval for a Mean Difference
6
Independent Samples t-test
THEORY
T
1.
Independent Samples t-test: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
Independent Samples t-test: Purpose, Hypotheses, and Assumptions
4
THEORY
T
3.
Independent Samples t-test: Test Statistic and p-value
PRACTICE
P
4.
Independent Samples t-test: Test Statistic and p-value
9
THEORY
T
5.
Confidence Interval for the Difference Between Two Independent Means
PRACTICE
P
6.
Confidence Interval for the Difference Between Two Independent Means
6
Independent Proportions Z-test
THEORY
T
1.
Independent Proportions Z-test: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
Independent Proportions Z-test: Purpose, Hypotheses, and Assumptions
4
THEORY
T
3.
Independent Proportions Z-test: Test Statistic and p-value
PRACTICE
P
4.
Independent Proportions Z-test: Test Statistic and p-value
9
THEORY
T
5.
Confidence Interval for the Difference Between Two Independent Proportions
PRACTICE
P
6.
Confidence Interval for the Difference Between Two Independent Proportions
2
Practical 8
THEORY
T
1.
Introduction
THEORY
T
2.
Testing for Differences Between Means
PRACTICE
P
3.
Two-sample t-test
6
THEORY
T
4.
Testing for Differences Between Proportions
PRACTICE
P
5.
Two-sample proportions test
6
THEORY
T
6.
Keypoints
9. Simple Linear Regression
Simple Linear Regression
THEORY
T
1.
Introduction to Regression
THEORY
T
2.
Simple Linear Regression
PRACTICE
P
3.
Simple Linear Regression
3
THEORY
T
4.
Finding the Regression Equation
PRACTICE
P
5.
Finding the Regression Equation
3
THEORY
T
6.
Residuals
PRACTICE
P
7.
Residuals
2
THEORY
T
8.
Assessing the Quality of a Regression Model
PRACTICE
P
9.
Assessing the Quality of a Regression Model
6
THEORY
T
10.
Statistical Inference in Regression
PRACTICE
P
11.
Statistical Inference in Regression
3
THEORY
T
12.
Inference about the Slope of a Linear Model
PRACTICE
P
13.
Inference about the Slope of a Linear Model
5
Practical 9
THEORY
T
1.
Introduction
PRACTICE
P
2.
Data Exploration - Quality of Life
4
THEORY
T
3.
Sum of Squared Residuals
PRACTICE
P
4.
Sum of Squared Residuals
2
THEORY
T
5.
Regression Line
PRACTICE
P
6.
Simple Linear Regression
5
THEORY
T
7.
Prediction and Prediction Errors
PRACTICE
P
8.
Prediction
1
THEORY
T
9.
Model Reliability and Validity of the Inference
PRACTICE
P
10.
Practice
7
THEORY
T
11.
Keypoints
10. Categorical Association
Chi-Square Goodness of Fit Test
THEORY
T
1.
Chi-Square Goodness of Fit Test: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
Chi-Square Goodness of Fit Test: Purpose, Hypotheses, and Assumptions
3
THEORY
T
3.
Chi-Square Goodness of Fit Test: Test Statistic and p-value
PRACTICE
P
4.
Chi-Square Goodness of Fit Test: Test Statistic and p-value
15
Chi-Square Test for Independence
THEORY
T
1.
Chi-Square Test for Independence: Purpose, Hypotheses, and Assumptions
PRACTICE
P
2.
Chi-Square Test for Independence: Purpose, Hypotheses, and Assumptions
2
THEORY
T
3.
Chi-Square Test for Independence: Test Statistic and p-value
PRACTICE
P
4.
Chi-Square Test for Independence: Test Statistic and p-value
12
Practical 10
THEORY
T
1.
Introduction to Cross Tables and Categorical Association
PRACTICE
P
2.
Data Exploration - Water Use
2
THEORY
T
3.
Cross Tables
PRACTICE
P
4.
Cross Tables
2
THEORY
T
5.
Chi-square Goodness of Fit Test
PRACTICE
P
6.
Chi-square Goodness of Fit Test
7
THEORY
T
7.
The Goodness of Fit Test on Repeat
PRACTICE
P
8.
Chi-square Goodness of Fit Test
1
THEORY
T
9.
Chi-square Test for Association
PRACTICE
P
10.
Chi-square Test for Association
6
THEORY
T
11.
Keypoints
Formulas, Statistical Tables and R Commands
Formulas
THEORY
T
1.
Formulas descriptive statistics
THEORY
T
2.
Formulas random variables
THEORY
T
3.
Formulas probability
THEORY
T
4.
Formulas regression
THEORY
T
5.
Formulas binomial distribution
THEORY
T
6.
Formulas normal distribution - z- and t-tests
THEORY
T
7.
Formulas analysis of variance (ANOVA)
THEORY
T
8.
Formulas cross tables
THEORY
T
9.
Formulas non-parametric tests
THEORY
T
10.
Formulas choosing tests
Statistical Tables
THEORY
T
1.
Table 1: Critical values z-distribution
THEORY
T
2.
Table 2: Critical values Student t-distribution
THEORY
T
3.
Table 3: Critical values chi-squared-distribution
THEORY
T
4.
Table 4: Critical values F-distribution
R commands
THEORY
T
1.
Overview of R commands
VVA Formula sheet
THEORY
T
1.
VVA Formula sheet I (Descriptive Statistics)
THEORY
T
2.
VVA Formula sheet II (Probability)
THEORY
T
3.
VVA Formula sheet III (Random Variables)
THEORY
T
4.
VVA Formula sheet IV (Probability and Sampling Distributions)
THEORY
T
5.
VVA Formula sheet V (Hypothesis Testing and Confidence Intervals)
THEORY
T
6.
VVA Formula sheet VI (Regression)
THEORY
T
7.
VVA overview R Commands
Quizzes
PRACTICE
P
1.
Theory Chapter 1
Unlock full access locked
PRACTICE
P
2.
Practical Chapter 1
Unlock full access locked
PRACTICE
P
3.
Theory Chapter 2
Unlock full access locked
PRACTICE
P
4.
Practical Chapter 2
Unlock full access locked
PRACTICE
P
5.
Theory Chapter 3
Unlock full access locked
PRACTICE
P
6.
Practical Chapter 3
Unlock full access locked
PRACTICE
P
7.
Theory Chapter 4
Unlock full access locked
PRACTICE
P
8.
Practical Chapter 4
Unlock full access locked
PRACTICE
P
9.
Theory Chapter 5
Unlock full access locked
PRACTICE
P
10.
Practical Chapter 5
Unlock full access locked
PRACTICE
P
11.
Theory Chapter 6
Unlock full access locked
PRACTICE
P
12.
Practical Chapter 6
Unlock full access locked
PRACTICE
P
13.
Theory Chapter 7
Unlock full access locked
PRACTICE
P
14.
Practical Chapter 7
Unlock full access locked
PRACTICE
P
15.
Theory Chapter 8
Unlock full access locked
PRACTICE
P
16.
Practical chapter 8
Unlock full access locked
PRACTICE
P
17.
Theory Chapter 9
Unlock full access locked
PRACTICE
P
18.
Practical Chapter 9
Unlock full access locked
PRACTICE
P
19.
Theory Chapter 10
Unlock full access locked
PRACTICE
P
20.
Practical Chapter 10
Unlock full access locked
Unlock full access  unlock

Open course on descriptive and inferential statistics with theory and interactive exercises.
Offered by the Teaching and Learning Centre of FNWI

Full access via UvAnetID

About us ⋅ Help ⋅ Privacy ⋅ Terms and conditions
Copyright © 2024 SOWISO