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What is Statistics?
What is Statistics?
Statistics is a branch of science that deals with the collection, presentation, organization, analysis, and interpretation of data.
Why should you study Statistics?
Why should you study Statistics?
What is a population?
What is a population?
A population encompasses all subjects, whether human or otherwise, that are being studied.
What is a sample?
What is a sample?
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Why do researchers rarely use the entire population in a statistical study?
Why do researchers rarely use the entire population in a statistical study?
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What is a parameter?
What is a parameter?
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What are the two branches of Statistics?
What are the two branches of Statistics?
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What does Descriptive Statistics involve?
What does Descriptive Statistics involve?
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What are some examples of what Descriptive Statistics include?
What are some examples of what Descriptive Statistics include?
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What does Inferential Statistics involve?
What does Inferential Statistics involve?
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What are some examples of what Inferential Statistics include?
What are some examples of what Inferential Statistics include?
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If a researcher wishes to conduct a social experiment on 100 students at their school, what is the population and sample size of this experiment?
If a researcher wishes to conduct a social experiment on 100 students at their school, what is the population and sample size of this experiment?
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If the researcher finds that 83% of the students in the experiment would return the money to the owner, is this Descriptive or Inferential statistics?
If the researcher finds that 83% of the students in the experiment would return the money to the owner, is this Descriptive or Inferential statistics?
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If the researcher uses the 83% of the students to create a confidence interval between 75% and 85%, is this Descriptive or Inferential statistics?
If the researcher uses the 83% of the students to create a confidence interval between 75% and 85%, is this Descriptive or Inferential statistics?
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What is the first step of the process of statistics?
What is the first step of the process of statistics?
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What is the second step of the process of statistics?
What is the second step of the process of statistics?
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If you are using a large sample to conduct your experiment, is inferential statistics still necessary?
If you are using a large sample to conduct your experiment, is inferential statistics still necessary?
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If a basketball player wants to know is average score over the last 10 games, what type of statistics would be used to answer this question?
If a basketball player wants to know is average score over the last 10 games, what type of statistics would be used to answer this question?
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If someone wants to use the average monthly electricity bill over the past year to predict the average monthly electric bill for the next year, what type of statistics would be used to answer this question?
If someone wants to use the average monthly electricity bill over the past year to predict the average monthly electric bill for the next year, what type of statistics would be used to answer this question?
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If a car manufacturer needs to find out the average lifespan of their car batteries by testing a sample of 50 batteries, what type of statistics would be used to answer this question?
If a car manufacturer needs to find out the average lifespan of their car batteries by testing a sample of 50 batteries, what type of statistics would be used to answer this question?
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If the data collected about 49% of individuals between 18 - 34 years old who have started employment is used to inform a report, what type of statistics would be used for this?
If the data collected about 49% of individuals between 18 - 34 years old who have started employment is used to inform a report, what type of statistics would be used for this?
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If a report uses data on the world population predicted in 2025, what type of statistics would be used for this?
If a report uses data on the world population predicted in 2025, what type of statistics would be used for this?
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What are the two types of variables?
What are the two types of variables?
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What is a Qualitative variable?
What is a Qualitative variable?
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What are the two types of Quantitative variables?
What are the two types of Quantitative variables?
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What is a Discrete variable?
What is a Discrete variable?
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What is a Continuous variable?
What is a Continuous variable?
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What are the four levels of measurement?
What are the four levels of measurement?
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What is the Nominal level of measurement?
What is the Nominal level of measurement?
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What is the Ratio level of measurement?
What is the Ratio level of measurement?
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What two main sources can be used to find documented data?
What two main sources can be used to find documented data?
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What are Primary Sources?
What are Primary Sources?
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What is Primary Data?
What is Primary Data?
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What are Secondary Sources?
What are Secondary Sources?
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What is Secondary Data?
What is Secondary Data?
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Which one of these options is NOT a method of collecting data?
Which one of these options is NOT a method of collecting data?
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What is a Census?
What is a Census?
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What is a Sample Survey?
What is a Sample Survey?
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What is a Respondent?
What is a Respondent?
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What is a Personal Interview?
What is a Personal Interview?
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What is a Telephone Interview or Video Call?
What is a Telephone Interview or Video Call?
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What are Self-Administered Questionnaires?
What are Self-Administered Questionnaires?
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What are Online Surveys?
What are Online Surveys?
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What is a Focus Group Discussion?
What is a Focus Group Discussion?
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What is an Experiment?
What is an Experiment?
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What is an Experimental Group?
What is an Experimental Group?
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What is a Control Group?
What is a Control Group?
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What is Observation?
What is Observation?
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What is Questionnaire?
What is Questionnaire?
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What are the two main types of questions presented in questionnaires?
What are the two main types of questions presented in questionnaires?
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What are Close-Ended Questions?
What are Close-Ended Questions?
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What is a Pitfall to avoid when wording questions?
What is a Pitfall to avoid when wording questions?
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What does It mean to avoid vague questions?
What does It mean to avoid vague questions?
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What does it mean to avoid confusing questions?
What does it mean to avoid confusing questions?
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What does it mean to avoid difficult questions?
What does it mean to avoid difficult questions?
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What does it mean to avoid sensitive questions?
What does it mean to avoid sensitive questions?
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What does it mean to keep questions short and simple?
What does it mean to keep questions short and simple?
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What are the two main categories of sampling techniques?
What are the two main categories of sampling techniques?
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What is Probability Sampling?
What is Probability Sampling?
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What are the four types of Probability Sampling?
What are the four types of Probability Sampling?
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What is Simple Random Sampling?
What is Simple Random Sampling?
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What is Stratified Sampling?
What is Stratified Sampling?
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What is Cluster Sampling?
What is Cluster Sampling?
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What is Systematic Sampling?
What is Systematic Sampling?
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What are the three types of Non-Probability Sampling?
What are the three types of Non-Probability Sampling?
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What is Convenience Sampling?
What is Convenience Sampling?
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What is Purposive Sampling?
What is Purposive Sampling?
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Study Notes
Introduction to Statistics
- Statistics is a branch of science dealing with the collection, presentation, organization, analysis, and interpretation of data.
- The term "statistics" originated from the Latin word "status," meaning state.
- Its early definition was the science dealing with data about a state or community's condition.
- Popular use of the term became common in the 19th century.
Why Study Statistics?
- Professionals need to read and understand various statistical studies in their fields.
- Statistical procedures are fundamental for research.
- Knowledge gained from studying statistics helps one become better consumers and citizens.
Population vs. Sample
- Population: All subjects in a study, be they human or otherwise.
- Sample: A group of subjects chosen from the population.
- Researchers rarely use the entire population due to cost, time, and practicality concerns.
Parameter vs. Statistic
- Parameter: A numerical measure describing characteristics of a population.
- Statistic: A numerical measure describing characteristics of a sample.
Branches of Statistics
- Descriptive Statistics: Organizing, summarizing, and presenting data through graphs, charts, tables, and summary calculations.
- Inferential Statistics: Making predictions and drawing conclusions about a population based on analyses of a sample.
Process of Statistics
- Identify research objective: Clearly define the question(s) you want answered.
- Collect information: Gather the needed information, often from a sample (subset of the population) due to practicality and cost.
- Organize and summarize: Descriptive statistics—organizing and describing the collected data (using charts, graphs, etc.).
- Draw conclusion: Inferential statistics—generalize the sample data to the broader population, estimating the reliability of this generalization.
- If the entire population is studied, inferential statistics is unnecessary.
Examples of Descriptive vs. Inferential Statistics
- Descriptive: Calculating an average score for 10 basketball games.
- Inferential: Forecasting next year's average electricity bill based on past bills.
- Descriptive: 49% of 18-34 year olds took a job due to the current economy.
- Inferential: Predicting the world's population in 2025.
Types of Variables
- Qualitative variables: Categorical variables based on characteristics or attributes (e.g., gender, religion).
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Quantitative variables: Numerical variables that can be counted or measured.
- Discrete: Variables that result from counting (e.g., number of siblings, students in a class)
- Continuous: Variables that can take on infinite possible values between any two points (e.g., height, weight).
Levels of Measurement
- Nominal: Categorical data without any inherent order (e.g., jersey numbers, eye color)
- Ordinal: Categorical data with an inherent order (e.g., rankings, satisfaction levels).
- Interval: Numerical data with meaningful differences but without a true zero point (e.g., temperature on Celsius/Fahrenheit, IQ).
- Ratio: Numerical data with meaningful differences and a true zero point (e.g., height, weight, age).
Collection of Data
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Sources of Data:
- Primary Sources: Data collected directly by the researcher or a research agency (e.g., Central Bank, Pulse Asia).
- Secondary Sources: Compiled data from other sources. (e.g., United Nations)
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Methods of Data Collection:
- Survey: Gathering data by asking questions (census or sample survey).
- Personal Interview: Interviewers ask questions and record responses.
- Telephone Interview/Video Call: Respondents answer questions over the phone.
- Self-Administered Questionnaires: Respondents answer questions without assistance.
- Online Surveys: Data collection via the internet.
- Focus Group Discussion: In-depth group discussions facilitated by a moderator.
- Experiment: The researcher controls conditions and variables in an experiment.
- Observation: Recording observations about a phenomenon as it naturally occurs.
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Questionnaire: A list of well-planned questions, either close-ended or open-ended
- Close-ended: pre-defined response options (e.g., multiple choice, rating scales)
- Open-ended: free-response questions that allow for details.
Sampling Techniques
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Probability Sampling: Each member of the population has a known chance of being selected.
- Simple Random Sampling, Stratified Sampling, Systematic Sampling, Cluster Sampling, Multistage Sampling
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Non-probability Sampling: The probability of each member being selected is unknown.
- Convenience Sampling, Purposive Sampling, Quota Sampling
Pitfalls to Avoid in Question Wording
- Avoid vague, biased, confidential, sensitive, too difficult, confusing, or perplexing questions.
- Keep questions short and to the point.
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Description
This quiz covers the fundamentals of statistics, including its definitions, importance in various fields, and key concepts such as population versus sample and parameter versus statistic. Understanding these concepts is essential for analyzing and interpreting data effectively.