1st Class Flashcards
What is Statistics?
It is a branch of mathematics that deals with collecting, analysing, interpreting, and presentation of numerical data.
Who needs to understand statistics and why is it important for them #1?
Researchers & research consumers -
- Stay informed
- Assess reliability and value of info (Evaluate Credibility & Usefulness)
- Make suitable choices. (Appropriate)
What are Statistics used for(Importance#2)?
- Predict future (diseases, Weather Forecasting)
- Determine probabilities (Planning)
- Answer questions based on numerical facts/measurements (Decision making)
- Facilitate comparisons
- Formulate & test hypothesis
- Simplify the message of figures.
What are Statistics used in?
- Medical Studies
- Understand natural phenomena
- Collecting quantitative data
- Insurance
- Diagnosing diseases in the medical field
- Govt policy and judgments
- Prepare for emergency
- Political campaigns
What is quantitative research?
- Process of collecting & analyzing numerical data.
- Used to find patterns and averages, make predictions, test casual relationships, and generalize results to wider populations.
What is Quantitative data?
- Quantitative data - information that can be quantified. It can be counted or measured and assigned a numerical value.
- Quantitative data - usually structured and appropriate for statistical analysis.
It targets a large sample, generally chosen via random sampling
What are the examples of Quantitative data; (Numerical)?
I. Height (Cm)
II. Weight (Kg)
III. Numbers, tests, counting, measuring
IV. Length (Cm)
V. Distance (Km)
VI. Number of days in a year
VII. Age
VIII. Income
IX. Number of errors
X. Group Size
What are the examples of Quantitative Research?
- Surveys
- Face-to-face paper surveys
- Online questionnaires
- Online polls
- Interviews
- Systematic observation
What is quantitative research?
- Process of collecting & analyzing numerical data.
- Used to find patterns and averages, make predictions, test casual relationships, and generalize results to wider populations.
What is Qualitative data?
It is collected and analyzed in a non-numerical form. It provides insights into the complexity of human experiences, motivations, and behaviors.
What are the Qualitative data; (Categorical)?
I. Gender
II. Religion
III. Marital Status
IV. Native Language
V. Social Class
VI. Qualifications
VII. Method Of Treatment
VIII. Type of Instruction
IX. Problem-Solving Strategy used
What are the examples of Qualitative Research?
I. 1 on 1 Interview
II. Focus Groups
III. Qualitative Observation
IV. Record Keeping
V. Case Study Research
VI. Ethnographic Research
What is primary data?
Collected first-hand by a researcher or a team of researchers for a specific research project or purpose.
What are examples of primary data?
- Customer surveys or questionnaires.
- Market research.
- Interview transcripts.
- Focus group transcripts.
- Observational data.
- Experimental data.
. Field trial data.
What are the advantages of primary data?
- Original
- Accurate
- Relevant to the topic
- Updated information
- Reliability of data
What are the disadvantages of primary data?
- Time consuming
- Costly
- Require more labour * Designing the questionnaire is a hardworking task
- Respondents may not give timely responses
- Answers may not reflect realities
What is secondary data?
Data collected by someone else earlier.
What are examples of Secondary data?
I. Tax records and social security data.
II. Census data
III. Electoral statistics.
IV. Health records.
V. Books, journals, or other print media.
VI. Government publications, websites, books, journal articles, internal records etc.
What are the advantages of secondary data?
I. Cost-efficient because it eliminates the cost of data collection.
II. Researchers save time because the data has already been collected, so they don’t have to collect new data.
III. Mostly easy to access most.
What are the disadvantages of secondary data?
I. Might be not specific to your needs. Secondary data is not specific to the researcher’s needs since it was collected in the past for another reason.
II. You have no control over data quality. The secondary data might lack quality.
III. Biasness.
IV. Not timely.
V. You are not the owner of the information.
VI. Data might not be reliable or accurate.
What are the ads and disads of Surveys and Questionnaires?
Advantages
I. Respondents - adequate time to give responses.
II. Free from the bias of the interviewer.
III. Cheaper compared to interviews.
Disadvantages
I. High rate of non-response bias.
II. Inflexible and can’t be changed once sent.
III. A slow process.
What are the ads and disads of Focus Groups (A Collection Method) ?
Advantages
I. Incurs a low cost compared to interviews. As the interviewer does not have to discuss with each participant individually.
II. Not time-consuming.
Disadvantages
I. Response bias - a participant might be subjective to what people will think about sharing a sincere opinion.
II. Group thinking - not mirror individual opinions.
What are the ads and disads of Interviews (A Collection Method)
Advantages
I. In-depth information can be collected.
II. Non-response and response bias can be detected.
III. Samples - can be controlled.
Disadvantages
I. More time-consuming.
II. Expensive.
III. Interviewer may be biased.
What are the ads and disads of Observation (A Collection Method) ?
Advantages
I. Data - usually objective.
II. Data (not affected by past or future events.)
Disadvantages
I. Information is limited.
II. Expensive
What are the ads and disads of Experiments (A Collection Method) ?
Advantages
I. Usually objective - data recorded are the results of a process.
II. Non-response bias is eliminated.
Disadvantages
I. Incorrect data may be recorded due to human error.
II. Expensive.
What are the Scales of measurement?
- Nominal Scales
- Ordinal Scales
- Interval Scales
- Ratio Scales
What are Nominal Scales?
- Nominal or categorical variables cannot be measured.
- Instead, we assign names and place them into categories.
What are the examples of categorical or nominal variables?
- City of birth
- Gender
- Ethnicity
- Car brands
- Marital status
- Blood group of patients
What are Ordinal Scales?
- Represents an ordered series of relationships or rank order, where the numbers do mean something.
- A type of categorical data where variables have natural, ordered categories.
What are the examples of Ordinal Scales?
- Top 5 Olympic medallists
- Language ability (e.g., beginner, intermediate, fluent)
- Likert-type questions (e.g., very dissatisfied to very satisfied)
What are Interval Scales?
- Fixed and equal intervals are assumed based on some accepted standards.
- They convey most information and give precise numerical quantitative measurements.
What are the examples of Interval Scales?
- Weight
- Height
- Time
- Money
- Test scores (e.g., IQ or exams)
- Personality inventories
- Temperature in Fahrenheit or Celsius
What are Ratio Scales?
- The highest level of measurement.
- Attributes - Can have categorize, rank, and equal intervals between neighboring data points, and there is a true zero point.
- Represents continuous values.
What are the examples of Ratio Scales?
- Height
- Age
- Weight
- Temperature in Kelvin (there are no negative degrees of temperature – zero means an absolute lack of thermal energy.)
