PRELIM LEC 1: INTRODUCTION TO STATISTICS Flashcards
are the basic sciences of public health
A. EPIDEMIOLOGY
B. BIOSTATISTICS
C. STATISTICS
D. INFERENTIAL STATISTICS
EPIDEMIOLOGY AND STATISTICS
is a BRANCH OF APPLIED MATHEMATICS which deals with the collection, organization, presentation, analysis and
interpretation of data
A. EPIDEMIOLOGY
B. BIOSTATISTICS
C. STATISTICS
D. INFERENTIAL STATISTICS
STATISTICS
is the APPLICATION OF STATISTICS to problems in the biological sciences, health, and medicine
A. EPIDEMIOLOGY
B. BIOSTATISTICS
C. STATISTICS
D. INFERENTIAL STATISTICS
BIOSTATISTICS
the study of the distribution and determinants of health, disease, or injury in human populations and the
application of this study to the control of health problems
A. EPIDEMIOLOGY
B. BIOSTATISTICS
C. STATISTICS
D. INFERENTIAL STATISTICS
EPIDEMIOLOGY
ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH
A. ADDRESS A PUBLIC HEALTH QUESTION
B. CONDUCTS A STUDY
C. COLLECT DATA
D. DESCRIBE THE OBSERVATION/DATA
E. ASSESS THE STRENGTH OF EVIDENCE FOR/AGAINST A HYPOTHESIS; EVALUATE THE DATA
F. RECOMMEND INTERVENTION OR PREVENTIVE PROGRAMS
used to estimate the EXTENT OF THE DISEASE in the population
A. SURVEY STUDY
B. SURVEILLANCE STUDY
C. OBSERVATIONAL STUDIES
D. EXPERIMENTAL STUDIES
A. SURVEY STUDY
investigate association between an exposure and a disease outcome
A. SURVEY STUDY
B. SURVEILLANCE STUDY
C. OBSERVATIONAL STUDIES
D. EXPERIMENTAL STUDIES
C. OBSERVATIONAL STUDIES
also investigate the association between an exposure, often therapeutic treatment, and disease outcome
A. SURVEY STUDY
B. SURVEILLANCE STUDY
C. OBSERVATIONAL STUDIES
D. EXPERIMENTAL STUDIES
D. EXPERIMENTAL STUDIES
is designed to MONITOR or DETECT
specific diseases
A. SURVEY STUDY
B. SURVEILLANCE STUDY
C. OBSERVATIONAL STUDIES
D. EXPERIMENTAL STUDIES
B. SURVEILLANCE STUDY
- methods provide an EXPLORATORY
assessment of the data from a study - deals with the collection and presentation of data and collection of SUMMARIZING values to DESCRIBE its group characteristics
INFERENTIAL STATISTICS OR DESCRIPTIVE STATISTICS ?
DESCRIPTIVE STATISTICS
- methods provide a CONFIRMATORY
data analysis - deals with PREDICTIONS and INFERENCES based on the analysis and interpretation of the results of the information gathered by the statistician
INFERENTIAL STATISTICS OR DESCRIPTIVE STATISTICS ?
INFERENTIAL STATISTICS
numerical characteristics or attribute associated with the population being studied
A. DATA
B. VARIABLE
C. SAMPLE
B. VARIABLE
Types of Variables:
example: Gender, Eye color, Blood
Type, Civil Status, Socio Economic
Status
A. Categorical or Qualitative Variables
B. Numerical - Valued or Quantitative
Variable
A. Categorical or Qualitative Variables
Types of Variables:
Numerical - Valued or Quantitative
Variables
- is a variable whose values are obtained by MEASURING such as temperature, distance, area, age, height
DISCRETE OR CONTINUOUS?
CONTINUOUS
Types of Variables:
Numerical - Valued or Quantitative
Variables
- is a variable whose values are obtained by COUNTING
DISCRETE OR CONTINUOUS?
DISCRETE
SCALES OF MEASUREMENT:
Sex, Nationality
A. ORDINAL SCALE
B. RATIO SCALE
C. NOMINAL SCALE
D. INTERVAL SCALE
NOMINAL SCALE
SCALES OF MEASUREMENT:
✔ ORDERED but differences between values are not important
✔ e.g., Likert scales, rank on a scale of 1..5 your degree of satisfaction
✔ e.g., pain ratings
A. ORDINAL SCALE
B. RATIO SCALE
C. NOMINAL SCALE
D. INTERVAL SCALE
ORDINAL SCALE
SCALES OF MEASUREMENT:
✔ ordered, constant scale, but NO NATURAL ZERO
✔ e.g., temperature (C,F)
A. ORDINAL SCALE
B. RATIO SCALE
C. NOMINAL SCALE
D. INTERVAL SCALE
D. INTERVAL SCALE
SCALES OF MEASUREMENT:
✔ ordered, constant scale, NATURAL ZERO
✔ e.g., height, weight, age, length
A. ORDINAL SCALE
B. RATIO SCALE
C. NOMINAL SCALE
D. INTERVAL SCALE
B. RATIO SCALE
is defined as groups of people, animals, places, things or ideas to which any conclusions based on characteristics of a sample will be applied
SAMPLE OR POPULATION?
POPULATION
subgroup of the population
SAMPLE
SLOVINS FORMULA
n= _____N_____
1 + N(e)2
STAGES IN THE SELECTION OF A SAMPLE
- Define the target population
- Select a sampling frame
- Determine id a probability or nonprobability sampling method
will be chosen - Plan procedure for selecting sampling units
- Determine sample size
- Select actual sampling units
- Conduct fieldwork
SAMPLING TECHNIQUE
- the SAMPLE is a PROPORTION (a certain percent) of the population and such sample is selected from the population by means of some systematic way in which every element of the population has a chance of being included in the sample
▪ RANDOMIZATION is a feature of the
selection process rather that an
assumption about the structure of the
population
▪ More complex, time consuming and
more costly.
NON - PROBABILITY OR PROBABILITY SAMPLING?
PROBABILITY SAMPLING
SAMPLING TECHNIQUE
- ▪ The SAMPLE is NOT A PROPORTION of the population and there is no system in selecting the sample. The selection DEPENDS UPON THE SITUATION.
▪ No assurance is given that each item has a chance of being included as a sample
▪ There is an assumption that there is an even distribution of characteristics within the population, believing that any sample would be representative
NON - PROBABILITY OR PROBABILITY SAMPLING?
NON - PROBABILITY SAMPLING
Probability Sampling:
This is the most popular and
simplest method (LOTTERY METHOD)
A. SYSTEMATIC SAMPLING/QUASI RANDOM SAMPLING
B. CLUSTER SAMPLING
C. SIMPLE RANDOM SAMPLING
D. STRATIFIED RANDOM SAMPLING
C. SIMPLE RANDOM SAMPLING
Probability Sampling:
the population is split into non - overlapping groups (“strata”), then simple random sampling is done on each group to form a sample
A. SYSTEMATIC SAMPLING/QUASI RANDOM SAMPLING
B. CLUSTER SAMPLING
C. SIMPLE RANDOM SAMPLING
D. STRATIFIED RANDOM SAMPLING
D. STRATIFIED RANDOM SAMPLING
Probability Sampling:
✔ This method is widely employed because of its ease and convenience.
✔ A frequently used method of sampling when a complete list of the population is available
A. SYSTEMATIC SAMPLING/QUASI RANDOM SAMPLING
B. CLUSTER SAMPLING
C. SIMPLE RANDOM SAMPLING
D. STRATIFIED RANDOM SAMPLING
A. SYSTEMATIC SAMPLING/QUASI RANDOM SAMPLING
Probability Sampling:
When the geographical area where the study is TOO BIG and the target population is TOO LARGE
A. SYSTEMATIC SAMPLING/QUASI RANDOM SAMPLING
B. CLUSTER SAMPLING
C. SIMPLE RANDOM SAMPLING
D. STRATIFIED RANDOM SAMPLING
B. CLUSTER SAMPLING
Non - Probability Sampling:
✔ no system of selection but only those whom the researcher or interviewer meet by chance are include the sample.
✔PICKING OUT PEOPLE in the most convenient and fastest way
✔ not representative of target population because sample are selected if they can be accessed EASILY AND CONVENIENTLY
✔ Advantage: EASY TO USE
✔ Disadvantage: BIAS IS PRESENT
✔ DELIVER ACCURATE RESULT when the population is HOMOGENOUS
CONVENIENCE SAMPLING
Non - Probability Sampling:
the respondents are chosen BASED ON THEIR KNOWLEDGE of the information desired
PURPOSIVE SAMPLING
PURPOSIVE SAMPLING:
specified number of persons of certain types are include in the sample.
QUOTA SAMPLING OR JUDGMENT SAMPLING ?
QUOTA SAMPLING
PURPOSIVE SAMPLING:
sample is taken based on certain judgements about the overall
population
QUOTA SAMPLING OR JUDGMENT SAMPLING ?
JUDGMENT SAMPLING
