Simplify the following descriptions for each term and give relevant examples
"bias: undetected influences, which can occur at any stage of the research process and which may alter or conceal the relationships between variables
causal relationship: a relationship between variables whereby variation in one variable leads directly to variation in another
constant: any property of an object or individual that does not vary from object to object or individual to individual
correlation: when two variables vary in the same way and we cannot determine whether a causal relationship exists between them, or whether they are both influenced by a third variable
cross-sectional study: a research study where all information is collected from participants at one point in time
dependent variable: a variable whose values change as a result of the influence of one or more other variables
descriptive study: a research study conducted when a researcher wishes to describe a phenomenon or behaviour
discourse analysis: a method of qualitative data analysis whereby a great deal of emphasis is placed on the role of language
explanatory study: a research study conducted when a researcher wishes to explain the relationship between variables, for example whether it is correlational or causal
exploratory study: a research study conducted when very little is known about a research topic
hypothesis: a speculative statement about the expected relationship between phenomena, which is then investigated empirically
independent variable: a variable whose values exert an influence on another variable
interval scale: a level of measurement that assigns numbers in such a way that the size of the difference between any two numbers corresponds to the size of the difference in the attribute being measured
longitudinal study: a research study where information is collected from participants over a period of time (e.g. every six months or every year for a fixed time period)
mean: a measure of central tendency that is an average score measure of central
median: a measure of central tendency that is the middlemost score when individual scores are ordered from lowest to highest
mode: a measure of central tendency that is the most commonly occurring score in a distribution of scores
multi-stage sampling (cluster sampling): a sampling procedure whereby researchers progress through a number of stages, randomly selecting clusters from the population at each stage until units of analysis are randomly selected in the final stage of sampling
narrative analysis: a method of qualitative data analysis whereby transcriptions from interviews or focus groups are approached as if they are a story following some form of sequence
negative correlation: the relationship that exists when two variables vary in opposite directions
nominal scale: a level of measurement that classifies variables into mutually exclusive groups that have numbers assigned to them
non-probability sampling: a sampling method where every unit of analysis in a population does not have an equal chance of being selected into a sample, and we do not know what the likelihood of each unit being selected is
ordinal scale: a level of measurement that assigns labels to variables in the form of numbers such that one variable can be placed in relation to another in terms of the quantity of the attribute that each possesses
positive correlation: the relationship that exists when two variables vary in the same direction
probability sampling: a sampling method where every unit of analysis in a population has an equal chance of being selected into a sample, and we know what the likelihood of each unit being selected is
qualitative research methods: research methods that obtain data in the form of descriptive narratives, in order to understand a phenomenon from the perspective of the research participant and gain an understanding of the meanings people give to their experiences
quantitative research methods: research methods that involve the application of statistical analysis to data, and the development of statistical approaches for measuring and explaining human behaviour
ratio scale: a level of measurement that assigns numbers in such a way that the size of the difference between any two numbers corresponds to the size of the difference in the attribute being measured (ratio scales cannot have negative numbers)
representative sample: a group of people, selected by a researcher from a population, who are in all ways similar to that population
sample: a collection of people or objects from which a researcher will collect information
sampling: a process employed by researchers whereby individuals or objects are selected to participate in a research study
semi-structured interview: a method for gathering information from research participants whereby the researcher ensures that certain areas of questioning are covered, but there is no fixed sequence or format of questions
structured interview: a method for gathering information from research participants whereby the researcher follows a set list and sequence of questions
thematic analysis: a method of qualitative data analysis whereby transcribed interviews or group discussions are broken down into units of meaning or themes
units of analysis: the objects from whom a researcher wants to collect information (they may be individuals, groups of people, organisations, periods of time and/or social artefacts)
unstructured interview (open-ended interview): a method for gathering information from research participants whereby the researcher merely tries to remain focused on an issue of study without any pre-set list of questions
variable: any property of an object or individual that can vary from person to person or object to object"
Bias: Hidden influences that can impact research results.
Example: A study on the benefits of a certain medication funded by the pharmaceutical company that produces it may be biased in favor of the drug.
Causal relationship: Relationship where changes in one variable directly affect another.
Example: The more hours a student studies, the higher their grades tend to be.
Constant: A property that does not change across different objects or individuals.
Example: The speed of light is a constant in physics.
Correlation: The relationship between variables that may or may not be causal.
Example: There is a correlation between ice cream sales and temperature, but it doesn't mean ice cream sales cause warmer weather.
Cross-sectional study: A study that collects data from participants at one specific time point.
Example: Surveying college students about their stress levels in a single semester.
Dependent variable: The variable that changes as a result of other variables.
Example: The amount of water a plant receives affects its growth (plant growth is the dependent variable).
Descriptive study: Research conducted to describe a phenomenon or behavior.
Example: Studying the eating habits of children aged 6-12.
Discourse analysis: Analyzing qualitative data with a focus on language.
Example: Analyzing political speeches to understand underlying messages and themes.
Explanatory study: Research conducted to explain relationships between variables.
Example: Investigating the impact of exercise and diet on weight loss.
Exploratory study: Research done when little is known about a topic.
Example: Examining the effects of a newly discovered substance on the human body.
Hypothesis: A statement speculating the relationship between phenomena.
Example: "If students study more, their test scores will improve."
Independent variable: Variable that influences others.
Example: The number of hours studied is the independent variable in determining test scores.
Interval scale: Assigns numbers so the differences between them are meaningful.
Example: Temperature measured in Celsius.
Longitudinal study: Research where data is collected over time.
Example: Tracking the same group of individuals over years to study changes in their behavior.
Mean: Average of all the scores.
Example: The mean of 5, 10, and 15 is 10.
Median: Middlemost score when arranged from lowest to highest.
Example: In the set 4, 5, 6, the median is 5.
Mode: Most frequently occurring score in a set of data.
Example: In the set 2, 3, 4, 4, 5, the mode is 4.
Multi-stage sampling: Method of sampling involving multiple steps.
Example: Randomly selecting states, cities, and neighborhoods in a study on education.
Narrative analysis: Qualitative data analysis treating data as a story.
Example: Analyzing personal stories of recovery from addiction.
Negative correlation: Variables that vary in opposite directions.
Example: As the hours of TV viewing increase, GPA tends to decrease.
Nominal scale: Classifies variables into exclusive groups with assigned numbers.
Example: Blood type being classified into categories like A, B, AB, O.
Non-probability sampling: Sampling where units do not have equal chances of selection.
Example: Using convenience sampling to survey people at a shopping mall.
Ordinal scale: Assigns labels to variables with numbers indicating quantity.
Example: Educational attainment levels like high school diploma, bachelor's degree, master's degree.
Positive correlation: Variables that vary in the same direction.
Example: More exercise leads to higher fitness levels.
Probability sampling: Sampling where every unit has an equal chance of selection.
Example: Using random sampling to survey households in a town.
Qualitative research methods: Obtaining descriptive data for understanding phenomena.
Example: Conducting interviews to explore experiences of cancer survivors.
Quantitative research methods: Applying statistical analysis to explain behavior.
Example: Conducting surveys to analyze the relationship between income and spending habits.
Ratio scale: Assigns numbers so differences are meaningful without negatives.
Example: Time measured in hours.
Representative sample: Group of people selected similar to the population.
Example: Surveying a random sample of adults to represent the population of a city.
Sample: Individuals or objects from which information is collected.
Example: 100 randomly selected students surveyed about their study habits.
Sampling: Process of selecting individuals or objects for a study.
Example: Randomly selecting households for a survey on recycling habits.
Semi-structured interview: Gathering information with some question guidelines.
Example: Interviewing teachers about their teaching methods with a list of topics.
Structured interview: Gathering information with a set list of questions.
Example: Interviewing job applicants with a fixed list of questions.
Thematic analysis: Dissecting qualitative data into themes or meanings.
Example: Analyzing interviews with teachers to identify common teaching practices.
Units of analysis: Objects from which information is collected.
Example: Studying the effects of climate change on individual coral reefs.
Unstructured interview: Gathering information without set questions.
Example: Having a casual conversation with a participant to gather insights.
Variable: A property that can vary across objects or individuals.
Example: Age, height, and weight are all variables.