Types of Analytics — roles?
Descriptive, predictive, prescriptive; analyze past, forecast, guide actions.
Data collection — purpose?
Gather and organize data for analysis and insights.
Population parameters — what?
True values describing entire population.
Sample statistics — purpose?
Estimate population parameters from samples.
Descriptive statistics — focus?
Summarize data using mean, median, mode.
Mean — definition?
Average of data points.
Median — role?
Middle value in ordered data.
Mode — function?
Most frequently occurring value.
Predictive analytics — use?
Forecast future outcomes using models.
Classification prediction — type?
Assign data to categories.
Regression prediction — outcome?
Estimate continuous numerical values.
Prescriptive analytics — purpose?
Recommend actions to influence future results.
Measures of central tendency — examples?
Mean, median, mode.
Variance — what?
Average squared deviation from mean.
Range — definition?
Difference between max and min.
Standard deviation — role?
Average distance from mean.
Sampling methods — types?
Simple random, stratified, systematic, cluster.
Nominal data — example?
Eye color, gender.
Ordinal data — example?
Rankings, education levels.
Interval scale — characteristic?
Equal intervals, no true zero.
Ratio scale — characteristic?
Equal intervals, true zero.
Outliers — effect?
Skew mean, less impact on median/mode.
Dispersion measures — examples?
Variance, standard deviation, range.
Influence of outliers — on mean?
Pulls mean toward extreme values.
Teste tes connaissances avec un QCM de 12 questions sur Fundamentals of Data Analytics.
1. What is predictive analytics?
2. What is the primary purpose of the data collection and storage process in data analytics?
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