Short course
SPSS
SPSS Statistics is one of the most widely used statistical analysis packages in research, public health, the social sciences and monitoring and evaluation. Its strength lies in its menu-driven interface: you get reliable results without writing a single line of code, which makes it accessible to users with no programming training and no taste for abstract mathematics.
- Duration
- 5 sessions, 18 hours
- Format
- In person or online
- Credential
- Certificate of attendance
Tuition49,000 XOF
By the end of the programme, you will be able to
- Navigate SPSS and understand the difference between Data View and Variable View
- Create a dataset from scratch and define each variable correctly
- Import a dataset from Excel, CSV, KoboToolbox or Google Forms
- Clean a dataset: missing values, duplicates, outliers, inconsistent codes
- Transform data: recoding, computing new variables, grouping into classes, weighting
- Produce the descriptive statistics suited to each type of variable
- Build cross-tabulations and custom tables ready to use in a report
- Carry out and interpret common statistical tests: chi-square, t-test, ANOVA, correlation
- Produce readable charts and export them to Word
- Write up a statistical result correctly, without over-interpreting
Who it is for
Target audience
The course is open to anyone, whatever their profession: final-year student, PhD student, researcher, monitoring and evaluation officer, health worker, civil servant, independent consultant or private sector employee. No profile is favoured and the fee is the same for everyone.
Prerequisites
Two requirements nonetheless apply:
- Hold the baccalaureate or an equivalent level, as the course assumes a minimum ease with numbers and percentages
- Have a personal laptop, on which the software will be installed during the first session
No prior knowledge of SPSS is required. No advanced knowledge of statistics is required either: the necessary theoretical concepts are explained as the course goes along, in plain language, at the moment they are needed.
Detailed program
5 sessions · 18 h of teaching
- Installing the software and activating the licence on each participant's computer
- What SPSS can do, what it cannot do, and when to prefer Excel or R
- The interface: the data window, the output window, the syntax window
- The fundamental difference between Data View and Variable View
- Creating a variable: name, type, width, decimals, label
- Value labels and why they determine the readability of all results
- Measurement levels: nominal, ordinal, scale, and how this choice affects the possible analyses
- Declaring missing values and distinguishing system-missing from user-missing
- Entering a dataset by hand and checking the entry
- Saving a data file in SAV format and understanding what it contains
- The SPV output file, its organisation and exporting it
- Guided exercise: create from scratch the dataset for a short ten-question questionnaire
- Importing a dataset from Excel: the pitfalls of headers, merged cells and date formats
- Importing a CSV file and handling separators and the encoding of accented characters
- Importing an export from KoboToolbox or Google Forms
- Checking the integrity of an imported dataset before any analysis
- Spotting and removing duplicates
- Detecting outliers and deciding what to do with them
- Handling missing values: spotting them, quantifying them, understanding their pattern
- Recoding a variable into a new variable, with or without changing categories
- Grouping a continuous variable into classes: ages, incomes, scores
- Computing a new variable with the expression builder
- Creating a score or composite index from several variables
- Selecting cases: filtering a subpopulation, working on a sample
- Sorting, splitting a file by group, merging two datasets by variables or by cases
- Weighting cases and understanding when weighting is essential
- Introduction to the syntax window: pasting a command, reading it, rerunning it, documenting your work
- Guided exercise: fully clean a raw survey dataset of three hundred observations
- Choosing the right statistic for the type of variable, the first decision in any analysis
- Counts and percentages: the Frequencies procedure
- Raw, valid and cumulative percentages, and which one to present
- Measures of central tendency: mean, median, mode, and when the mean lies
- Measures of dispersion: standard deviation, variance, range, quartiles, interquartile range
- The Descriptives procedure and the Explore procedure
- Checking the normality of a distribution: histogram, box plot, Shapiro-Wilk test
- Cross-tabulations: building, reading, choosing between row, column or total percentages
- The Custom Tables procedure to produce a table ready for publication
- Statistics by subgroup with the Means procedure
- Charts: bar chart, pie chart, histogram, box plot, scatter plot
- Choosing the representation that fits the message and avoiding misleading charts
- Formatting a chart in the chart editor
- Cleanly exporting tables and charts to Word without losing formatting
- Guided exercise: produce the complete descriptive section of a survey report
- What a statistical test is and what question it really answers
- Null hypothesis, alternative hypothesis, significance level, the p-value and its correct interpretation
- The most common mistake: confusing statistical significance with practical importance
- Choosing your test: the decision tree based on the type and number of variables
- The chi-square test of independence: conditions of use, reading the result, adjusted residuals
- Measures of association for categorical variables: Cramér's V, contingency coefficient
- The independent-samples t-test and its non-parametric alternative, the Mann-Whitney test
- The paired-samples t-test and the Wilcoxon test
- One-way analysis of variance and post hoc multiple comparison tests
- The non-parametric alternative to ANOVA, the Kruskal-Wallis test
- Pearson and Spearman correlation, and the distinction between correlation and causation
- Introduction to simple linear regression: fitted line, coefficient, model quality
- Writing the interpretation of a test result in a report or dissertation
- The most common interpretation errors and how to avoid them
- Guided exercise: answer four research questions on a real dataset, from choosing the test to writing it up
- Each participant works on their own dataset, brought on the day
- Individual scoping: which questions the dataset can really address
- Step-by-step support in cleaning and preparing this dataset
- Choosing the relevant analyses in light of the participant's objectives
- Carrying out the analyses and checking the conditions of use of the tests
- Reviewing the results produced and correcting mistaken interpretations
- Formatting the tables and charts for the report or dissertation
- The trainer works individually with each participant throughout the session
- Participants without a dataset of their own work on a dataset provided, choosing from three themes
Assessment and certification
There is no final assessment in this course. As the training is short and intensive, it aims to build practical skills, not to validate a level through an exam.
A training attestation is given to each participant at the end of the fifth session. It is issued by Waaldé Impact, signed by the trainer, and states the course title, the 18-hour duration, the dates and the list of modules followed. It certifies actual participation in the course.
Upcoming sessions
Next dates being prepared
Leave your email: we will let you know as soon as registration opens.
Frequently asked questions
49,000 XOF per participant. Training for a team or an organisation is quoted on request.
5 sessions, 18 hours.
Yes: you can attend onsite or online, as you prefer.
Two requirements nonetheless apply: hold the baccalaureate or an equivalent level, as the course assumes a minimum ease with numbers and percentages ; have a personal laptop, on which the software will be installed during the first session ; no prior knowledge of SPSS is required. No advanced knowledge of statistics is required either: the necessary theoretical concepts are explained as the course goes along, in plain language, at the moment they are needed.
A certificate of attendance is issued at the end of the course.
Fill in the online enrolment request: no payment is taken on the site. The firm reviews your application, then contacts you to confirm your place and the payment terms. No session is scheduled yet: leave your email on this page to be told when registration opens.
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