Midsemester Exam

BOMDAS/BODMAS

Order of operations: Brackets → Orders → Multiply/Divide → Add/Subtract.

Squaring a number

Squaring a number removes its sign (e.g., (-3)² = 9).

Mean formula

Mean is calculated as  X̄ = ∑X / N.

Ubiquity of statistics

Statistics are essential across various fields like clinical practice, HR, sports psychology, marketing, and media literacy.

Mathematics anxiety

Mathematics anxiety can be mitigated by understanding that statistics uses basic math concepts and software for complex calculations.

Psychology breadth

Psychology includes 56 APA divisions covering various specialized fields.

Peer-review process in research

The peer-review process involves manuscript submissions, expert reviews, revisions, and publication.

Core knowledge sources

Key sources are personal experience, authority, reason, and empiricism.

Scientific method essentials

Science is a process involving rationalism and empiricism, focusing on observation and testable questions.

Scientific theory

A well-formed scientific theory summarizes existing facts and provides an explanatory mechanism.

Falsifiable hypothesis

A hypothesis must be falsifiable, meaning it should provide conditions under which it could be disproven.

Operational definition

Precise descriptions of how variables are measured or manipulated.

Converging operations

Using multiple methods or definitions to confirm a construct's validity.

Random variability

Random variability refers to inherent differences among individuals that can obscure effects.

Random assignment

Random assignment ensures that each participant has an equal chance of being assigned to any group.

Control groups

Control groups are used in experiments to isolate the effect of the independent variable.

Quasi-experimental design

Quasi-experimental designs do not use random assignment and often analyze pre-existing groups.

Correlational design

A correlational design examines relationships between naturally varying variables without manipulation.

Null hypothesis (H0)

The null hypothesis states there is no relationship between the independent variable and dependent variable.

Alternative hypothesis (H1)

The alternative hypothesis states there is a relationship between the independent variable and dependent variable.

Independent variable (IV)

The variable that is manipulated by the experimenter.

Dependent variable (DV)

The variable that is measured and is presumed to be influenced by the independent variable.

Variability in data

Variability includes random variability, individual differences, and situational variables affecting measurement.

Confounding variables

Confounding variables vary systematically with the IV and threaten causal interpretation.

Extraneous variables

Extraneous variables can contribute to variability in the DV and obscure effects.

Control of variability

Methods to control variability include random assignment and matching participants.

Ethics in research

Ethics focused on the moral treatment of research participants and adherence to ethical guidelines.

Pilot testing

Pilot testing involves verifying that measures function as intended before main data collection.

Descriptive statistics

Descriptive statistics summarize and describe data characteristics, including measures of central tendency.

Inferential statistics

Inferential statistics generalize findings from a sample to a larger population.

Frequency distribution

A frequency distribution shows the number of occurrences of different values in a dataset.

Normal distribution

A normal distribution is bell-shaped and symmetric, important in statistical analysis.

Skewness

Skewness measures asymmetry in a distribution; positive or negative skew indicates tail direction.

Kurtosis

Kurtosis measures the 'tailedness' of a distribution, affecting variance interpretations.

Central tendency

Central tendency measures include mean, median, and mode that describe typical values.

Standard deviation (SD)

Standard deviation quantifies the amount of variation or dispersion in a set of values.

Variance

Variance represents the average of the squared differences from the mean, indicating variability.

Percentiles

Percentiles indicate the value below which a percentage of observations fall in a dataset.

Box-and-whisker plot

A box-and-whisker plot is used to summarize data distribution and identify outliers.

Bar graph

A bar graph displays categorical data with rectangular bars representing frequency counts.

Histogram

A histogram presents frequency distribution for continuous data with touching bars.

Data cleaning

Data cleaning involves rectifying errors and ensuring dataset accuracy before analysis.

Cumulative frequency

Cumulative frequency accumulates counts up to each point in a frequency distribution.

Operational definitions for memory

Memory operationally defined as the ability to recall words after a specific period.

Measurement error

Measurement error refers to inaccuracies in data collection affecting results.

Research design

Research design outlines procedures for conducting systematic investigations and data collection.

Variables in research

Variables are characteristics measured in studies, including independent, dependent, and extraneous types.

Research ethics

Research ethics ensures that studies are conducted fairly and with respect for participants.

Theories vs. hypotheses

A theory is a broad explanatory framework; a hypothesis is a testable prediction derived from a theory.

Null and alternative hypothesis definitions

Null (H0) means no effect; alternative (H1) indicates a potential effect or relationship.

Research replication

Research replication tests whether findings hold true under similar conditions and methods.

Statistical significance

Statistical significance assesses whether observed effects are unlikely to occur by chance.

Conceptual framework

A conceptual framework defines the relationships between concepts in a research study.

Research integrity

Research integrity involves conducting studies honestly and without bias.

Statistical power

Statistical power is the probability of correctly rejecting a false null hypothesis.

Subjective vs. objective measurement

Subjective measurement relies on personal judgment; objective measurement relies on observable data.

Qualitative vs quantitative research

Qualitative research explores concepts; quantitative research tests hypotheses using numerical data.

Causal inference

Causal inference determines if changes in an IV directly result in changes in a DV.

Descriptive analysis

Descriptive analysis summarizes data to provide insights about central tendency and variability.

Statistical models

Statistical models mathematically represent relationships between variables in studies.

Experimental control

Experimental control refers to minimizing extraneous factors to establish clear effects.

Statistical sampling

Statistical sampling involves selecting a subset from a population to assess its characteristics.

Randomized controlled trial (RCT)

RCT is a type of experimental study used to test the effectiveness of interventions.

Blind vs double-blind study

In blind studies, participants don't know their group; in double-blind studies, neither participants nor researchers know.

Analysis of variance (ANOVA)

ANOVA is a statistical method used to compare means among multiple groups.

Confidence interval

A confidence interval estimates the range in which a population parameter is likely to fall.

Statistical hypothesis testing

Statistical hypothesis testing evaluates the evidence against the null hypothesis.

Multicollinearity

Multicollinearity occurs when independent variables are highly correlated, complicating analysis.

Outliers

Outliers are data points that differ significantly from other observations in a data set.

Regression analysis

Regression analysis examines relationships between dependent and independent variables.

Chi-square test

The chi-square test assesses the association between categorical variables.

Effect size

Effect size quantifies the strength of a response to an experimental manipulation.

Null effect

A null effect indicates no significant difference or relationship observed in data analysis.

Data integrity

Data integrity ensures the accuracy and reliability of data throughout a study.

Practicality in research

Practicality entails considering feasibility and resources when designing experiments.

Statistical software

Statistical software aids in conducting analyses, managing data, and generating visualizations.

Time-order relationship

A time-order relationship is necessary to establish causality between two variables.

Independent measures design

Independent measures design involves different participants for each condition in an experiment.

Field study

A field study examines subjects in their natural environment, offering real-world insights.

Placebo effect

The placebo effect is a psychological phenomenon where participants experience perceived benefits from a treatment due to expectations.

Field experiments

Field experiments manipulate variables in real-world settings while maintaining control of extraneous factors.

Longitudinal study

A longitudinal study collects data over a longer period to observe changes and developments.

Cross-sectional study

A cross-sectional study examines participants at a single point in time, comparing different groups.

Blinding in research

Blinding prevents participant or researcher knowledge of group assignments to reduce bias.

Institutional Review Board (IRB)

An IRB oversees research ethics and protects participants' rights and welfare.

Statistical significance threshold

The statistical significance threshold typically set at p < 0.05 indicates a 5% chance of error.

Slope of a regression line

The slope represents the change in the dependent variable for each unit change in the independent variable.

Data visualization

Data visualization utilizes graphical representations to simplify complex data for analysis.

Quantitative techniques

Quantitative techniques use numerical data and statistical methods for analysis.

Qualitative techniques

Qualitative techniques explore non-numeric data to understand concepts and experiences.

Effectiveness of treatments

Effectiveness of treatments examines the real-world impact of interventions on outcomes.

Sample bias

Sample bias occurs when a sample is not representative of the population, affecting generalizability.

Test validity

Test validity determines how well a test measures what it intends to measure.

Psychometric properties

Psychometric properties assess reliability and validity of psychological measures.

Statistical generalization

Statistical generalization applies findings from a study sample to a broader population.

Research limitations

Research limitations acknowledge constraints that can affect study interpretations and validity.

Accountability in research

Accountability in research involves transparency, responsible conduct, and ethical practices.

Sampling methods

Sampling methods include random, stratified, and cluster sampling to select study participants.