Basic statistics - a full course
5.0
(3)
29 learners
What you'll learn
- Distinguish between populations and samples and choose appropriate descriptive statistics such as mean, median, mode, range, and standard deviation for summarising data
- Calculate and interpret confidence intervals and apply the correct t-test (one-sample, independent, or paired) to draw conclusions from sample data
- Perform hypothesis testing by defining null and alternative hypotheses, calculating p-values, and interpreting results while accounting for Type 1 and Type 2 errors
- Select and execute
This course includes
- 8.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 48 lessons • 8.5 hours of video
Basic statistics - a full course
48 lessons
• 8.5 hours
Basic statistics - a full course
48 lessons
• 8.5 hours
- Population vs Sample 06:41
- Mean, median and mode 09:14
- Range, interquartile range (IQR) and box plots 08:29
- Standard deviation | how to calculate the SD and variance 08:05
- Why do we divide by n-1 and not n? | shown with a simple example | variance and sd 10:14
- The normal distribution | how to interpret and use it 15:00
- The central limit theorem | Explained with a simple example 09:19
- The standard error of the mean (SEM)| how to calculate and interpret | SE vs SD 09:16
- Confidence intervals - simply explained 12:52
- The t-distribution - why we need it | explained with confidence intervals 15:44
- The one-sample t-test and p-values 10:22
- t-test VS confidence intervals 11:50
- The degrees of freedom - explained with a simple example 02:56
- The basic steps of hypothesis testing 08:25
- The unpaired t-test | Independent samples t-test 16:18
- The paired t-test | explained with a simple example 11:26
- Paired vs unpaired t-test 05:02
- One-way ANOVA: the basics 14:44
- One-way ANOVA: the calculations - step-by-step 13:41
- The repeated-measures ANOVA | explained with a simple example 13:02
- The geometric mean 07:07
- Variables and scales in statistics 05:52
- One-proportion Z-test and the corresponding confidence interval 12:30
- The Chi-square goodness of fit test | and the difference to the one-proportion Z-test 10:39
- The two proportion z-test and the Chi-square test of homogeneity 12:31
- The Chi-square test of independence VS homogeneity and goodness of fit 06:00
- The McNemar test 04:56
- The Mann Whitney U test (Wilcoxon Mann Whitney test) part 1/2 12:09
- The Mann Whitney U test (Wilcoxon Mann Whitney test) part 2/2 | exact p-value 10:27
- The Wilcoxon signed-rank test & the sign test 10:57
- The basics of type 1 and 2 errors | explained with a simple example 12:42
- The probability of making a type 1 error 06:40
- The probability of making a type 2 error | explained with a simple example (part 1/2) 14:18
- The probability of making a type 2 error | explained with a simple example (part 2/2) 08:50
- Statistical power and sample size calculations 15:32
- p-values - a deeper understanding | alpha | t-statistics 13:24
- Correlation - the basics | Pearson correlation 12:40
- Correlation | hypothesis testing | assumptions 07:28
- Spearman's rank correlation | Pearson VS Spearman 08:05
- Linear regression | the basics - for beginners 14:22
- Least squares - explained with a simple numeric example 11:34
- Linear regression | hypothesis testing 09:50
- Linear regression | the R-squared value 08:41
- Assumptions in Linear Regression - explained | residual analysis 16:35
- Multiple linear regression - explained with two simple examples 15:08
- Permutations Combinations and the Hypergeometric distribution 13:08
- Fisher's test and how to calculate the exact p-value 13:03
- How to choose an appropriate statistical test 18:36
Take this course with you
Download the app to continue lessons from your phone anytime.
