GCSE Statistics CCEA
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25 topics in 5 modules
☑️ Data Collection 5 topics
- Types of data: qualitative, quantitative (discrete, continuous), primary, secondary
- Data collection methods: sampling methods, questionnaires, interviews
- Sampling: random, systematic, stratified, cluster, multistage, quota, convenience
- Errors in surveys: coverage error, nonresponse error, sampling error, measurement error
- Minimizing errors in data collection
☑️ Data Presentation and Interpretation 5 topics
- Tables: frequency and cumulative frequency tables, contingency tables, summary statistics
- Graphs and charts: bar charts, histograms, line graphs, pie charts, box plots, stem and leaf plots, scatter plots
- Central tendency measurements: mean, median, mode
- Measures of dispersion: range, interquartile range, variance, standard deviation
- Calculation of quartiles, percentiles, and deciles
☑️ Probability 5 topics
- Basic concepts: sample space, events, probability axioms
- Probability of simple events
- Compound events: independent and dependent events, conditional probability
- Probability tree diagrams and tables
- Probability distributions: binomial, geometric and Poisson distributions
☑️ Statistical Analysis 5 topics
- Correlation: Spearman’s rank correlation coefficient, product moment correlation coefficient (PMCC)
- Association between categorical data: Chi-squared test for independence, contingency tables and its interpretation
- Regression: linear regression, least squares regression line
- Time series analysis: moving averages, trends, seasonal variation, cyclical variation, irregular variation
- Index numbers: simple index numbers, weighted index numbers, consumer price index (CPI)
☑️ Statistical Inference 5 topics
- Estimation: point estimates and interval estimates, confidence intervals
- Hypothesis testing: null hypothesis, alternative hypothesis, test statistics, p-value
- Tests for means and proportions: one-sample and two-sample t-tests, z-tests
- Testing difference between means of paired data
- Analysis of variance (ANOVA): one-way and two-way
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GCSE Statistics CCEA Revision Content
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GCSE Statistics CCEA - Data Collection - Types of data: qualitative, quantitative (discrete, continuous), primary, secondary Content Preview
Data Collection
Types of data: qualitative, quantitative (discrete, continuous), primary, secondary
Types of Data
Qualitative Data
- Qualitative data refers to non-numerical information that is typically descriptive in nature.
- It can take the form of words, pictures, objects, symbols, and other observable characteristics.
- Examples might include colours, tastes, textures, smells, and sounds.
- In a statistical context, it often involves classifying or categorising individuals or items into groups.
- It's often collected through methods like interviews, focus groups, and direct observation.
Quantitative Data
- Quantitative data is numerical information that can be measured or counted.
- It lends itself well to statistical analysis, as you can perform various mathematical and statistical calculations.
- It's usually presented in the form of numbers, percentages, averages, or other statistical measurements.
Discrete Quantitative Data
- With discrete quantitative data, values can only take specific, separate values.
- This type of data is countable and often includes things like the number of siblings a person has or the number of cars in a parking lot.
Continuous Quantitative Data
- Continuous quantitative data can take on any value within a given range.
- These values often have a logical order or sequence and can be subdivided into ever-smaller units.
- Examples include height, weight, temperature, and time.
Primary Data
- Primary data is data that you collect yourself, specifically for the purpose of your investigation.
- These collection methods can include surveys, interviews, and direct observations.
- This data is often more reliable and relevant to the study at hand, but it can be time-consuming to collect and process.
Secondary Data
- Secondary data is data that was collected by someone else and is already publicly available.
- This could include government records, research studies, newspaper articles, and web content.
- This kind of data can be very useful in saving time and resources, but you need to be careful to ensure it is reliable, accurate, and relevant to your investigation.
Question: What type of data is represented when a statistician is recording the heights of every student in a classroom?
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