Chemistry: SC1-10 Statistics for Chemists
Wed 15 Jan, Mon 20 Jan, ... Mon 10 Feb 2020
Description
This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course.
Target audience
- Chemistry postgraduate students
- Further details regarding eligibility criteria are available
- If you are from outside the Department of Chemistry, please arrive 15 minutes early and wait to be collected from reception
Sessions
Number of sessions: 8
# | Date | Time | Venue | Trainer | |
---|---|---|---|---|---|
2 | Wed 15 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
3 | Mon 20 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
4 | Wed 22 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
5 | Mon 27 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
6 | Wed 29 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
7 | Mon 3 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
8 | Wed 5 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
9 | Mon 10 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | G30 | map | Matt Castle |
Objectives
- Introducing R and RStudio, familiarise participants with software; R interface and scripts; Calculations; Variables; Functions; Data Structures.
- Data Visualisation, Manipulation and Summaries.,Importing and exporting real data; Interrogating dataframes; Plotting and visualisation techniques; Extracting summary statistics.
- Comparing up to two samples, overview of hypothesis testing; One and two sample hypothesis tests; Binomial test; Chi-squared test (extrinsic and intrinsic); Fisher’s exact test; One sample t-test; Student’s t-test; Mann-Whitney test; paired t-test; Wilcoxon signed-rank test.
- Comparing more than two samples, one-way analysis of variance (ANOVA); Assumptions for ANOVA (Shapiro-Wilk test, Bartlett’s test, Wald-Wolfowitz test); Kruskal-Wallis test.
- Comparing two continuous variables, Pearson’s product-moment correlation coefficient; Spearman’s rank correlation coefficient; Simple linear regression; Assumptions of linear regression.
- Multiple Predictor Variables, categorical predictors with continuous response: Two-way ANOVA; Categorical and continuous predictors with continuous response: Blending ANOVA and regression.
- Linear Model Framework -Continuous response variables, multiple predictor variables; Constructing and interpreting linear models; Revisiting ANOVA and regression; Model selection; stepwise regression and AIC
- Logistic regression and Generalised Linear models.
- Experimental Design, Errors, power, randomization, replication, good and bad designs, determining sample size, power analysis
- Analysing Data and Writing Statistical Reports
Bringing everything together in a systematic fashion., structuring statistical analyses and presenting results clearly.
Duration
- Eight sessions of two hours
Frequency
- Yearly
Theme
Statistics for Chemists
Booking / availability