Unit 1: Introduction Statistical Biology Flashcards
- A vital language and tool in almost all aspects of our daily life.
- A group of methods used to collect, analyze, present, and interpret data and to make decisions.
Statistics
Decisions made by using statistical methods.
Educated guesses
Decisions made without using statistical or scientific methods.
Pure guesses
Deals with the development, derivation, and proof of statistical theorems, formulas, rules, and laws.
Mathematical/Theoretical statistics
Involves the application of those theorems, formulas, rules, and laws to solve real-world problems (e.g. economics, psychology, public health).
Applied statistics
Consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures.
Descriptive statistics
Consists of methods that use sample results to help make decisions or predictions about a population from a sample.
Inferential statistics
Examples of Descriptive statistic
- Bar charts, pie charts, and line charts.
- Numerical tables.
- Rates.
The branch of applied statistics directed toward applications in the health sciences and biology.
Statistical Biology/Biostatistics
- A specific subject of object (e.g. a person, a company, a state, or country) about which the information is collected.
- This can also be called an observational unit.
Element or member of a sample or population
A characteristic under study that assumes different values of different elements.
Variable
The value of a variable for an element.
Observation or Measurement
A collection of observations on one or more variables.
Data set
Results when a single variable is measured. Example: body temperature of 150 people.
Univariate data
Results when two variables are measured. Example: body temperature and age of 150 people.
Bivariate data
Results when more than two variables are measured.
Multivariate data
The collection of all elements–individuals, items, or objects–whose
characteristics are being studied.
Population
The collection of a number of elements selected from a population. It is a subset selected from the target population.
Sample
The collection of information that includes every member of the population.
Census
The collection of information from the elements of a sample.
Sample survey
A numerical measure that summarize data for an entire population.
Parameter
A a numerical measure that summarize data from a sample.
Statistcs
A method of sampling in which each member of the population has some chance of being selected in the sample.
Random sampling
A method of sampling in which some member of the population may not have any chance of being selected in the sample.
Nonrandom sampling
The most accessible members of the population are selected to obtain the results quickly.
Convenience sampling
The members are selected from the population based on the judgment and prior knowledge of an expert.
Judgement sampling
A statistical error that occurs when an analyst does not select a sample that represents the entire population of data.
Sampling error
Can occur both in a sample survey and in a census. Such errors occur because of human mistakes and not chance.
Non-sampling errors
- The error that occurs because the sampling frames is not representative of the population.
- When we need to select a sample, we use a list of elements from which we draw a sample, and this list usually does not include many members of the target population.
Selection error
- The error that occurs because many of the people included in the sample do not respond to a survey.
- The sample are representative of the population, nonresponse error may occur because many of the people included in the sample may not respond to the survey.
Non-response error
- Occurs when people included in the survey do not provide correct answers.
- This or bias occurs when the answer given by a person included in the survey is not correct.
Response error
- The polls conducted based on samples of readers of magazines and newspapers suffer from voluntary response error or bias.
- Occurs when a survey is conducted on a randomly selected people but on a questionnaire published in a magazine or newspaper and people are invited to respond to that questionnaire
Voluntary Response Error
Used to obtain a random sample that represents the target population.
Random sampling techniques
A sampling technique in which any particular sample of a specific sample size has the same chance of being selected as any other sample of the same size.
Simple Random Sampling
The number of elements in the sample, denoted by n.
Sample size
Denoted by N, is the number of elements in the population.
Population size
For example, if we need to select 5 students from a class of 50 (target population), we write each of the 50 names on a separate piece of paper. Then, we place all 50 names in a bowl and mix them thoroughly. Next, we draw 1 name randomly from the bowl. We repeat this experiment four more times. The 5 drawn names make up a simple random sample with a sample size of 5.
Lottery or fishbowl sampling
A sampling technique in which the elements of the sample are taken from every kth element in the population arranged alphabetically or by other characteristic. Here, k = 𝑁/𝑛 .
Systematic Random Sampling
A sampling technique in which the entire population is divided into smaller groups that are not overlapping and represent the entire population.
Stratified Random Sampling
A sampling technique in which the entire population is divided into multiple groups usually by geographical area.
Cluster random sampling
May be classified as quantitative or qualitative.
Variable
Variables that can be measured numerically. These variables are collected in quantitative data such as income, height, gross sales, price of a home, number of cars owned, and a number of accidents.
Quantitative or Numeric variables
A variable whose values are countable with no possible intermediate values between consecutive values.
Discrete variable
A variable that can assume any numerical value between two numbers.
Continuous variable
A variables that cannot be measured numerically can be divided into different categories.
Qualitative or categorical variables
A data collected on different elements at the same point or for the same period of time.
Cross-section data
A data collectedonthesameelementof the same variable at different points or for different period of time.
Time-series data
A manual computations in statistics involve a lot of adding all values of the variable.
Summation notation.
Used to denote the sum of all values.
Uppercase Greek letter Σ (pronounced sigma)
