Core Statistical Concepts: Data, Inference & Models

Understanding Data Types

Different types of data require different analytical approaches:

  • Cross-sectional data: Characteristics of many subjects or observations at the same point in time.
  • Time series data: Data focusing on one observation over several time periods.
  • Cross-sectional time series data: A collection of observations for multiple subjects at multiple time periods.
  • Panel or longitudinal data: The same subject measured over various time periods.

Quantitative Data

Quantitative data is numerical.

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Probability Questions and Solved Examples

Here is the giant combined cheat sheet with all questions, tables, charts, calculations, and answers included. You can copy this into a document editor and save it as a PDF.

Probability Questions and Answers

Question 1

Statement: Tossing a coin and getting a head, and then rolling a 6-sided die and getting a 5. Are these events dependent?

Answer: False

Explanation: The events are independent because the outcome of the coin toss does not affect the die roll.

Question 2

Which pairs of events are disjoint?

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Statistics Problems and Solutions

1. Blood Cholesterol Analysis

Blood cholesterol was measured on a random sample of 24 people:

226, 189, 240, 192, 216, 207, 221, 255, 190, 237, 219, 182, 209, 198, 243, 202, 234, 194, 213, 185, 193, 223, 204, 191

i) Stem-and-Leaf Plots

The first 18 observations have been entered in the stem-and-leaf plot on the left. The completed plot is shown on the right.

Left Plot (Original Entries in Bold) | Right Plot (Ordered)

25 | 5 | 25 | 5

24 | 0 3 | 24 | 0 3

23 | 7 4 | 23 | 4 7

22 | 6 1 3 | 22 | 1 3 6

21 | 6 9

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Research Methods: A Comprehensive Study

Side 1: Chapter 4 – Research Design

Definition

The plan or blueprint for a study, outlining how data will be collected and analyzed.

Types

  • Exploratory
  • Descriptive
  • Causal

Key Research Design Types

Exploratory Research

Conducted when little is known, aims to gain insights and clarify ideas.

Descriptive Research

Provides a detailed description of phenomena, without manipulation.

Causal Research

Establishes cause-and-effect relationships between variables.

Sampling Design

Probability Sampling

Every member of the population

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Key Concepts in Statistics: Data, Methods & Limitations

Limitations of Statistics

  • Statistics does not deal with individuals:
    • Statistics deals with an aggregate of facts and does not give specific recognition to individual items in a series.
    • It deals with groups of individuals and indicates the characteristics of the whole group.
  • Statistics does not deal directly with qualitative characteristics:
    • Statistical methods can only be applied to numerically expressed data.
    • A qualitative phenomenon must be converted into quantitative information before statistical
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Understanding Statistical Variability and Distributions

Understanding Measures of Variability

Measures of variability indicate how much scores in a distribution vary, either from the mean or across the full extent of the distribution. It represents the spread of all the scores. Four measures of variability are discussed here: the range, the average mean deviation, the variance, and the standard deviation. These measures can reveal the consistency or similarity of the scores in a distribution and the extent to which the mean truly represents all of the

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