UFOR 231 lesson 1 - Intro to statistics

Learning objectives

1. Demonstrate

2. Categorize data by type and level of measurement

3. Identify the four basic sampling techniques

4. Define with your own words, and put into context, all the terms in the glossary

Statistics

• Science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data.

Descriptive Statistics

• Consists of the collection, organization, summary and presentation of data; does not draw any conclusions.

• I.e. the average mark of students not doing their homework is 45%

Inferential statistics

• Consists of generalizing from samples to population, estimations and hypothesis tests, relationships among variables, and predictions

• Students who do their homework have a 90% chance of passing.

Population

• Consists of all subjects that are being studied

Sample

• Group of subjects that are selected from a population.

Statistic

• Characteristic or measure obtained by sing the data values from a sample.

Parameter

• Characteristic or measure obtained by using all the data values from a specific population

Variable

• Characteristic or atrtribute tcan assume different values

Data

• Values (measurements or observations) that the variables can assume

Data value or observation

• Individual value of a variable

Qualitative variables

• Can be laced into distinct categories

Quantitative variables

• Numerical and can be ordered, ranked or measured

Discrete variables

• Variables that can be counted

Continuous variables

• Can assume an infinite number of values in an interval between any two specific values

Measurement levels or scales:

• Qualitative or quantattive variables that can be classified with how they are categorized, counted or measured

Nominal level

• Classifies data into mutually exclusive (non-overlapping) categories in which no order or ranking can be imposed on the data. Typically used for qualitative variables

Ordinal level

• Classifies data into categories that can be ranked; however, no precise differences between the ranks exist

Interval level

• Ranks data and precise differences between units of measure do exist, however, there is no meaningful zero.

Ratio level

• Possess all the characteristics of interval scale and a true zero exists. In addition, true ratios exist when the same variable is measured on two different members of the population.

What does data collectiion techniues depend on?

• Situation, logistics, budget, target error, etc.

Examples of data collection techniques examples

• Telephone surveys, mailed questionnaires, internet surveys, forest inventory plots, remote sensing, etc.

What is the main objective of data collection techniues?

• To obtain unbiased samples.

Overview of sampling methods

• Random selection method

• Stratified selection method

• Systematic selection method

• Cluster stelection method

Random selection method

• Subjects are selected randomly (using random numbers)

Stratified sectiion method

• Subjects are sleected by diving subjects into strata or sections

Systemattic subject selection

Subjects are selected by using every kth number after the first subject is randomly selected

Cluster subject selection

• Subjects are selected by using an intact group that is representative of the population

Glossary of terms

• Cluster sampling

• Continuous variable

• Data

• Data value

• Descriptive statistics

• Discrete variable

• Inferential statistics

• Interval level

• Measurement level

• Nominal level

• Observation

• Ordinal level

• Parameter

• Population

• Random sampling

• Ratio level

• Sample

• Sampling method

• Scale

• Statistic

• Stratified sampling

• Systematic sampling

• Variable