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STA-102: The Ultimate Statistics Power Guide — From Data Basics to Hypothesis Mastery

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This comprehensive statistics glossary provides a complete foundation for understanding key statistical concepts, formulas, and analytical methods used in data interpretation and research. It explains essential terms such as population, sample, mean, median, and mode, while differentiating between qualitative and quantitative data types. The guide explores scales of measurement, variability measures like range, variance, and standard deviation, and detailed descriptions of statistical distributions including the normal curve and Z-scores. It also delves into advanced concepts such as correlation, regression, and hypothesis testing—helping learners grasp how data drives decision-making and prediction. Designed for students, researchers, and professionals, this reference blends theory, formula application, and interpretation to provide a clear, practical understanding of statistics in the real world.

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STA-102: The Ultimate Statistics Power Guide —
From Data Basics to Hypothesis Mastery
Temperature - 00C, 37.5K

Ratio - true zero has no value - it has an absolute zero

Population - group of people, animals, places, things, or ideas to which any conclusions based
on characteristics of a sample will be applied

Sample - a subgroup of the population

Parameter - A numerical measure that describes a population.

Statistic - A numerical measure that describes a sample.

Descriptive Statistics - deals with describing the important characteristics of a given
data.

Inferential Statistics - It is a process by which we infer population properties from sample
properties.

Mean - The total value of an observation in a data set divided by the number of all
observations.

Median - the middle value in distribution when the values are arranged in ascending or
descending order

Mode - The most commonly (frequent) occurring value in a distribution or data set.

Ungrouped data - means data is raw that is not sorted or classified yet into categories.

Summation - adding all the numbers or given data

Qualitative Data - uses categories or attributes that are distinguished by some non-numeric
characteristics.

Quantitative Data - consist of numbers representing counts or measurements.

Discrete Data - quantitative data which can assume a finite or countable number of
values.

, Continuous Data - quantitative data which can assume infinity of many possible
values.

Primary data - refer to information which is gathered directly from the original source.

Secondary data - refer to information which is taken from a secondary source.

Range - It is the simplest measure of variation.

Variable - a numerical characteristic or attribute associated with the population being
studied.

Mean Absolute Deviation (MAD) - Is the average of how much the data values differ from the
mean.

Scales of Measurement - refer to ways in which variables/numbers are defined and
categorized.

Nominal - classifies elements into two or more categories or classes

Ordinal - a scale by rank or order

Interval - zero has a value - no absolute zero in this scale

Bimodal - 2 modes

Trimodal - 3 modes

Unimodal - one mode

MAD - Mean Absolute Deviation; average distance from mean.

Variance - Measure of data dispersion; calculated from squared deviations.

Standard Deviation - Square root of variance; indicates data spread.

Quantiles - Values dividing data into equal parts; also fractiles.

Quartiles - Divides data into four equal parts; Q1, Q2, Q3.

Deciles - Divides data into ten equal parts; D1 to D10.

Percentiles - Divides data into hundred equal parts; P1 to P100.

Inter-Quartile Range - Difference between Q3 and Q1; measures middle 50%.

Quantile Deviation - Measures variability using quartiles; QD = (Q3-Q1)/2.

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