1. Population VS Sample
1.1. Population
1.1.1. Consists of all elements -- individuals, items, or objects -- whose characteristics are being studied
1.2. Sample
1.2.1. A portion of the population selected for study
2. Sources of data
2.1. Internal sources
2.1.1. Data taken from the records of the organization itself, such as a company’s personnel files, accounting records etc
2.2. External sources
2.2.1. Data taken from the sources outside the organization
2.2.2. Consists of
2.2.2.1. Primary data
2.2.2.1.1. Data that are published or released by the same organization that collected them.
2.2.2.2. Secondary data
2.2.2.2.1. Data that are published by an organization but the data are collected by other organization
2.3. Surveys and experiments
3. Sample Surveys and Sampling Techniques
3.1. Survey
3.1.1. The collection of information from the elements of a population or a sample
3.2. Census
3.2.1. A survey that includes every member of the population
3.3. Sample Survey
3.3.1. A survey that includes elements of a sample
4. Methods of survey
4.1. Observation
4.1.1. Decisions concerning local traffic flow are based on observations of flow made by video cameras or teams of observers
4.2. Questionnaire
4.2.1. Face-to-face interview
4.2.2. By post
4.2.3. By phone
5. Sampling and Nonsampling errors
5.1. Sampling errors
5.1.1. the difference between the result obtained from a sample survey and the result that would have been obtained if the whole population had been included in the survey
5.2. Nonsampling errors
5.2.1. The errors that occur in the collection, recording, and tabulation of the data
5.2.2. Examples
5.2.2.1. Response error
5.2.2.2. Selection error
5.2.2.3. Nonresponse error
5.2.2.4. Voluntary response error
6. Type of variables and data
6.1. Quantitative variable
6.1.1. A variable whose values can be measured numerically
6.1.2. Types
6.1.2.1. Discrete variable
6.1.2.1.1. A variable whose values are countable and usually integer-valued.
6.1.2.1.2. Can assume only certain values with no intermediate values.
6.1.2.2. Continuous variable
6.1.2.2.1. A variable whose values cannot take exact value.
6.1.2.2.2. Assume any numerical value over a certain interval or intervals.
6.2. Qualitative or Categorical variable
6.2.1. A variable that cannot assume a numerical value but can be classified or ranked into two or more nonnumeric categories.
6.2.2. Types
6.2.2.1. Nominal variable
6.2.2.1.1. Defined categories
6.2.2.2. Ordinal variable
6.2.2.2.1. Ordered categories
7. Cross-Section Data VS Time-Series Data
7.1. Cross-section data
7.1.1. Data collected on different elements at the same point in time or for the same period of time.
7.2. Time-series data
7.2.1. Data collected on the same element for the same variable at different points in time or for different periods of time.
8. Pilot study / survey
8.1. Carried out before the real survey in order to test the questionnaire
8.2. The aim is to find and overcome any difficulties before using the real questionnaire.
9. Definition of Statistics
9.1. Numerical facts
9.2. The field or discipline of study
9.2.1. a science of collecting, analyzing, presenting and interpreting data and draw conclusions from the data
10. Types of statistics
10.1. Descriptive Statistics
10.1.1. Consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures
10.1.2. Deals with the description and analysis of a given group of data
10.2. Inductive Statistics
10.2.1. Consists of methods that use sample results to make decisions or predictions about a population
10.2.2. Deals with the problems of making inferences or drawing conclusions about population based on information obtained from the samples taken from the population
11. Why Sample?
11.1. Save time
11.2. Save cost
11.3. Impossibility of conducting a census
12. Samples and types of samples
12.1. Probability/random samples
12.1.1. Simple Random Sampling
12.1.1.1. Every indidividual or item from the frame have the equally chance to be selected
12.1.2. Systematic Random Sampling
12.1.2.1. Decide on sample size n
12.1.2.2. Divide frame of N individuals into k groups of individuals
12.1.2.3. Randomly select one individual from the 1st group
12.1.2.4. Select k-th individuals afterwards
12.1.3. Stratified Random Sampling
12.1.3.1. Divide population into 2 or more strata according to some common characteristics
12.1.3.2. A simple random sample is selected from each strata
12.1.3.3. Samples are combined into one
12.1.4. Cluster Sampling
12.1.4.1. Population is divided into several clusters, each representative of the population
12.1.4.2. A simple random sample of clusters is selected
12.1.4.3. All items in the selected clusters can be used, or items can be chosen from a cluster using another probability sampling technique
12.2. Non Probability/Non-Random Samples
12.2.1. Convenience
12.2.1.1. the most accessible members of the population are selected
12.2.2. Judgement
12.2.2.1. the members are selected from the population based on the judgment or prior knowledge of an expert
13. Basic Terms
13.1. Element Or Member
13.1.1. A specific subject or object about which the information is collected.
13.2. Variable
13.2.1. A characteristic under study that assumes different values for different elements.
13.3. Observation or measurement
13.3.1. The value of a variable for an element.
13.4. Data Set
13.4.1. A collection of observations on one or more variables.
14. Measurement scales
14.1. Nominal Scale
14.1.1. Classifies data into distinct categories without ranking
14.2. Ordinal Scale
14.2.1. Classifies data into distinct categories without ranking
14.3. Interval Scale
14.3.1. Ordered scale in which the difference between measurements is a meaningful quantity but the measurements doesn't have a true zero point
14.4. Ratio Scale
14.4.1. Ordered scale in which the difference between measurements is a meaningful quantity and the measurements have a true zero point
15. Steps in statistical investigation
15.1. State the problem / study clearly
15.2. Preparation of questionnaire
15.3. Selection of the sample (sampling)
15.4. Data collection
15.5. Editing the questionnaire
15.6. Organization and presentation of data
15.7. Analysis and interpretation of data
15.8. Report writing
16. Questionnaires
16.1. The design of questionnaire
16.1.1. Consists of 2 parts.
16.1.1.1. The first part requires the details of the respondent
16.1.1.2. The second part consists of the questions related to the investigation
16.2. The characteristics of a good questionnaire
16.2.1. Questions should be short and simple
16.2.2. Questions should be free from unfamiliar words
16.2.3. Leading questions (questions that guide to the answer) should be avoided
16.2.4. Questions should not require any calculations to be made
16.2.5. If possible, the questions will need the precise answer
16.2.6. An objective question is preferable to a subjective question