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Mon 11 Jan, Wed 13 Jan, ... Wed 3 Feb 2021
10:00 - 12:00

Provided by: Department of Chemistry


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Chemistry: SC1-10 Statistics for Chemists

Mon 11 Jan, Wed 13 Jan, ... Wed 3 Feb 2021

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.

Once you book this course, you will need to register for each session via Zoom.

Target audience
  • Chemistry postgraduate students
  • Further details regarding eligibility criteria are available
Sessions

Number of sessions: 8

# Date Time Venue Trainer
1 Mon 11 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
2 Wed 13 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
3 Mon 18 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
4 Wed 20 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
5 Mon 25 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
6 Wed 27 Jan   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
7 Mon 1 Feb   10:00 - 12:00 10:00 - 12:00 Dr Matt Castle
8 Wed 3 Feb   10:00 - 12:00 10:00 - 12:00 Dr 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