Flashcard: Fundamentals of Data Analytics — 24 carte

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.