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Summary

REVIEWER FOR STATS...

Description

Statistics -

Branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data.

SIGNIFICANCE - helps you use the proper methods to collect the data, employ the correct analyses, and effectively present the results.

2 FIELDS/ DIVISION 1. DESCRIPTIVE STATISTICS - The goal is to describe. Numerical measures are used to tell about features of a set of data. - Average - Correlation - Range or standard deviation - Graphical 2. INFERENTIAL STATSTICS - produced through complex mathematical calculations that allow scientists to infer trends about a larger population based on a study of a sample taken from it. Scientists use inferential statistics to examine the relationships between variables within a sample and then make generalizations or predictions about how those variables will relate to a larger population. - Hypothesis testing

KINDS OF DATA 1. NUMERICAL DATA [Quantitative]- These data have the meaning as a measurement. - DISCRETE DATA - represent items that can be counted.

- CONTINUOUS DATA - represent measurements. 2. CATEGORICAL DATA - Categorical data represent characteristics. 2 SOURCES OF DATA 1. Primary data – first hand; based on observation and interview. 2. Secondary data – edited interview [manuscript]

METHODS OF COLLECTING DATA 1. INTERVIEW – Direct 2. QUESTIONNAIRE – Survey; indirect 3. REGISTRATION – class registration

4. OBSERVATION use senses 5. EXPERIEMENTATION if there are not enough data to collect

Collection of data/ how to prepare data 1. Collection 2. Presentation

3. Analysis 4. Interpretation

Scales of Measuring Data 1. Nominal Scale - used for labeling variables, without any quantitative value. “Nominal” scales could simply be called “labels.”

2. Ordinal Scale - the order of the values; typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.

3. Interval Scale - are numeric scales; quantitative

4. Ratio Scale - scales give us the ultimate–order, interval values, plus the ability to calculate ratios since a “true zero” can be defined.

POPULATION - is a finite or infinite collection of objects, events or individuals with specified class or characteristics under consideration.

SAMPLE - finite or limited collection of objects, events, or individuals selected from a population. 1. RANDOM – Not everybody can be a subject  LOTTERY OR FISHBOWL – simply writing the names or numbers of all the individual members in a small- rolled piece of papers, then placed in a container.

 TABLE OF RANDOM – These tables show sets of random digits arranged in groups.  Direct Selection Method  The Remainder Method

 SYSTEMATIC RANDOM SAMPLING – Involves the selection of the desired sample in a list by arranging them systematically. 𝑘 =

𝑁 𝑛

 STRATIFIED RANDOM SAMPLING – Stratified sampling is a type of sampling method in which the total population is divided into smaller groups or strata to complete the sampling process. The strata are formed based on some common characteristics in the population data. After dividing the population into strata, the researcher randomly selects the sample proportionally.  Simple Stratified  Stratified Proportional

 Multi-stage or Multiple Sampling - divides large populations into stages to make the sampling process more practical. A combination of stratified sampling or cluster sampling and simple random sampling is usually used.

2. Non – Random sampling – everybody can be a subject.  Judgement or purposive or authoritative - most effective in situations where there are only a restricted number of people in a population who own qualities that a researcher expects from the target population; chosen only on the basis of the researcher’s knowledge and judgment.

 Quota - researchers create a sample involving individuals that represent a population. Researchers choose these individuals according to specific traits or qualities.

 Cluster – a probability sampling technique where researchers divide the population into multiple groups (clusters) for research.

 Accidental [Convenience] - is where you include people who are easy to reach.  Methods of Presenting Data 1. Textual 2. Tabular 3. Graphs 

Line graph, Circle graph or Pie chart, Pictogram or Picture graph, Map graph or Cartogram



Bar graph, Scatter point diagram...