Week 3 Overview
| Dates | 03 February 2025 - 07 February 2025 |
| Reading | Required: SCIU4T4 Workbook chapters 9-12 |
| Recommended: Navarro and Foxcroft (2022) Chapter 5 and Chapter 4.1 | |
| Suggested: Rowntree (2018) Chapter 3 | |
| Advanced: None | |
| Lectures | 3.0: Decimal places and significant figures part 1 (7:52 min; Video) |
| 3.1: Decimal places and significant figures part 2 (7:08 min; Video) | |
| 3.2: Graphs (10:29 min; Video) | |
| 3.3: Box-whisker plots (8:07 min; Video) | |
| 3.4: The mean (16:52 min; Video) | |
| 3.5: The mode (6:54 min; Video) | |
| 3.6: The median and quantiles (8:04 min; Video) | |
| 3.7: Mean, mode, median, and resistance (8:35 min; Video) | |
| 3.8: The variance (9:40 min; Video) | |
| 3.9: The standard deviation (6:17 min; Video) | |
| 3.10: Other measures of spread (7:46 min; Video) | |
| 3.11: Standard error (13:23 min; Video) | |
| Lecture | Careers session: 05 FEB 2025 (WED) 09:00-10:00 Cottrell LT B4 |
| Practical | Plotting and statistical summaries (Chapter 14) |
| Room: Cottrell 2A15 | |
| Group A: 05 FEB 2025 (WED) 10:00-13:00 | |
| Group B: 06 FEB 2025 (THU) 15:00-18:00 | |
| Help hours | Brad Duthie |
| Room: Cottrell 2Y8 | |
| 07 FEB 2025 (FRI) 14:00-16:00 | |
| Assessments | Week 3 Practice quiz on Canvas |
Week 3 focuses on descriptive statistics, how to report them, interpret them, and communicate them with graphs.
Chapter 9 focuses on how to interpret numbers with the correct degree of accuracy and precision. In practice, this means interpreting values with the correct number of digits (decimal places and significant figures), and rounding appropriately. It is important to ensure that data are not interpreted or reported has having a higher degree of accuracy or precision than is justified by measurement. This chapter provides numerical examples and shows the number of decimal places and significant figures for each, and it provides instructions and examples for how to round to a specific number of significant figures.
Chapter 10 introduces different types of graphs for communicating data visually. The chapter focuses specifically on histograms, pie charts, barplots, and box-whisker plots. It explains what type of plot is appropriate for a given type of variable (see Chapter 5). Specifically, histograms are shown to be applied to continuous data. Barplots and pie charts are shown as useful for categorical data (with a preference for barplots in most cases in the biological and environmental sciences), and box-whisker plots (i.e., boxplots) are presented as a means to show summary statistics for multiple variances simultaneously.
Chapter 11 introduces the first type of summary statistics with measures of central tendency. These are measures that describe the centre of the data using a single number. Measures of central tendency in this chapter include the mean, the mode, the median, and quantiles. For each measure of central tendancy, examples are provided with real numbers, and new mathematical notation is introduced to explain the mean (summation and indexing). The ways in which the word ‘mode’ is used are explained, and instructions are given with examples for calculating the median and quantiles.
Chapter 12 introduces measures of spread. In contrast to measures of central tendency, which focus on the centre of a dataset, measures of spread focus on how much the data are spread out. Measures of spread in this chapter include the range, the inter-quartile range, the variance, the standard deviation, the coefficient of variation, and the standard error. For all measures of spread, an example with real numbers is provided. The range is first explained as the maximum value of a variable minus the minimum value. Inter-quartile range (IQR) is then explained as the third quartile minus the first quartile. A considerable amount of text is then used to explain the variance, with a focus on calculating the sum of squares and the need to account for correct degrees of freedom. Degrees of freedom is then explained in general terms. The standard deviation and the coefficient of variation are then presented with a brief explanation of when and why they are used. Lastly, the standard error is explained and noted as being a bit different from the other measurements in that it is measuring the standard deviation of the sample means around the true mean.
Chapter 13 explains the concepts of skew and kurtosis, and statistical moments. This chapter emphasises how to recognise from a histogram when data are left or right skewed, or when data are leptokurtic or platykurtic. It also explains why the second, third, and fourth moments identify the variance, skew, and kurtosis, respectively. The third and fourth moment are shown in the context of the equation for variance to help link the key concepts of this chapter with prior material.
Chapter 14 is a guide to using jamovi for making plots introduced in Chapter 10, specifically histograms and box-whisker plots. It also focuses on finding measures of central tendency and spread introduced in Chapter 11 and Chapter 12, respectively, in jamovi, and reporting them accurately using the knowledge from Chapter 9. Five exercises are introduced in total. These exercises use hypothetical measurements of petiole diameter from the white water lily (Nymphaea alba), which is found in different sites across Scotland. Exercises rely on the Descriptives option in jamovi for plotting and calculating summary statistics.