UGC NET Psycology Research Methodology and Statistics Syllabus

Differentiate naturalistic observation from participant observation.

Naturalistic observation records behavior in its natural setting without intervention; participant observation involves the researcher joining and interacting within the group being studied.

What is the Hawthorne effect in observational/survey research?

The tendency of participants to alter their behavior simply because they know they are being observed or studied.

What is the main distinguishing feature of a true experimental design?

Manipulation of an independent variable, presence of a control group, and random assignment of participants to conditions, allowing causal inferences.

How does a quasi-experimental design differ from a true experiment?

A quasi-experiment manipulates an IV and has comparison groups but lacks random assignment, using pre-existing/intact groups, which weakens causal inference.

What is a survey research method best suited for?

Collecting standardized self-report data (attitudes, opinions, behaviors) from a sample via questionnaires or interviews to describe and generalize to a larger population.

What characterizes a cross-cultural study?

Comparing two or more cultural groups on psychological variables to examine cultural similarities/differences and the influence of culture on behavior; concerned with etic vs emic distinctions.

Distinguish the etic and emic approaches in cross-cultural research.

Etic studies behavior from outside, using universal/culture-general categories for comparison; emic studies behavior from within a single culture using culture-specific meanings.

What is the central aim of phenomenological research?

To describe and understand the lived experience and essence of a phenomenon from the perspective of those who experienced it, often via bracketing (epoché) of researcher assumptions.

What is the defining feature and goal of grounded theory?

Systematically generating a theory grounded in (derived inductively from) data through constant comparison and theoretical sampling until theoretical saturation is reached.

List the three main coding stages in grounded theory analysis.

Open coding (identifying concepts), axial coding (relating categories and subcategories), and selective coding (integrating around a core category).

What is a focus group as a qualitative method?

A guided group discussion (typically 6-12 participants) led by a moderator to explore attitudes, perceptions, and experiences, generating data through group interaction.

What does narrative research focus on?

Studying the stories people tell about their lives and experiences, analyzing their structure, content, and meaning to understand identity and how people make sense of events.

What is a case study and what is its main strength and weakness?

An in-depth, holistic investigation of a single individual, group, event, or unit. Strength: rich, detailed understanding; Weakness: limited generalizability and potential for researcher bias.

What is the defining method and aim of ethnography?

Prolonged immersion (fieldwork) in a culture or community, using participant observation to describe and interpret its shared patterns of behavior, beliefs, and language.

Define the three measures of central tendency and when each is preferred.

Mean (arithmetic average; best for interval/ratio, symmetric data), Median (middle value; best for skewed data/ordinal), Mode (most frequent; best for nominal data).

Why is the median preferred over the mean for skewed distributions?

The median is resistant to extreme scores (outliers), whereas the mean is pulled toward the tail of a skewed distribution, distorting the typical value.

Name the main measures of dispersion from least to most informative.

Range, interquartile range (IQR/quartile deviation), variance, and standard deviation.

What is the standard deviation, and how does it relate to variance?

The standard deviation is the average distance of scores from the mean; it equals the positive square root of the variance (variance = mean of squared deviations).

List the key properties of the Normal Probability Curve.

Symmetric and bell-shaped; mean = median = mode at center; asymptotic tails; total area = 1; defined by mean and SD; mesokurtic (kurtosis = 3).

State the empirical (68-95-99.7) rule for the normal curve.

About 68% of scores fall within ±1 SD of the mean, ~95% within ±2 SD, and ~99.7% within ±3 SD.

Distinguish positive skew, negative skew, and the kurtosis terms leptokurtic and platykurtic.

Positive skew: tail to the right (mean > median); negative skew: tail to the left (mean < median). Leptokurtic: peaked, heavy tails; platykurtic: flat, light tails (vs mesokurtic = normal).

What assumptions distinguish parametric tests from non-parametric tests?

Parametric tests assume normality, homogeneity of variance, and interval/ratio data; non-parametric (distribution-free) tests make no such distributional assumptions and suit ordinal/nominal data or small/skewed samples.

Give the non-parametric equivalents of the independent t-test, paired t-test, and one-way ANOVA.

Independent t-test → Mann-Whitney U; paired t-test → Wilcoxon signed-rank; one-way ANOVA → Kruskal-Wallis H.

When is a chi-square test used?

With categorical (nominal/frequency) data to test goodness-of-fit (one variable) or independence/association between two categorical variables.

Define statistical power and state its conventional desired level.

Power is the probability of correctly rejecting a false null hypothesis (1 − β), i.e., detecting a true effect; the conventional minimum desired level is 0.80.

List the four factors that influence statistical power.

Sample size (n), effect size, significance level (alpha), and the variability/error in the data (and whether the test is one- or two-tailed).

Define Type I and Type II errors.

Type I error (alpha): rejecting a true null hypothesis (false positive); Type II error (beta): failing to reject a false null hypothesis (false negative).

What is effect size and name one common measure for mean differences and one for correlation.

Effect size quantifies the magnitude/strength of a relationship or difference independent of sample size. For mean differences: Cohen's d; for association: r (or eta-squared/r² for variance explained).

State Cohen's conventions for small, medium, and large values of d.

d ≈ 0.2 (small), 0.5 (medium), 0.8 (large).

What does the Pearson product-moment correlation coefficient (r) measure, and what is its range?

The strength and direction of a linear relationship between two continuous variables; it ranges from −1.00 (perfect negative) through 0 (no linear relation) to +1.00 (perfect positive).

Match these special correlation methods to their data: Spearman's rho, point-biserial, phi, biserial.

Spearman's rho: two ranked/ordinal variables; point-biserial: one continuous and one true dichotomy; phi (φ): two true dichotomies; biserial: one continuous and one artificial dichotomy.

What is the coefficient of determination (r²) and what does it represent?

r² is the square of the correlation coefficient; it represents the proportion of variance in one variable that is accounted for/explained by the other.

What is the purpose of regression analysis, and what does the regression coefficient (b) indicate?

Regression predicts a dependent variable from one or more predictors. The slope coefficient b indicates the expected change in Y for a one-unit change in X.

In the regression equation Y = a + bX, what do 'a' and 'b' represent?

'a' is the intercept (predicted value of Y when X = 0); 'b' is the slope/regression coefficient (rate of change in Y per unit X).

What is multicollinearity in multiple regression and why is it problematic?

High intercorrelation among predictor variables; it inflates standard errors, makes coefficient estimates unstable, and obscures the unique contribution of individual predictors.

What is the goal of factor analysis?

A data-reduction technique that identifies underlying latent dimensions (factors) explaining the pattern of intercorrelations among a large set of observed variables.

Differentiate exploratory factor analysis (EFA) from confirmatory factor analysis (CFA).

EFA explores data to discover the number and nature of factors without a prior hypothesis; CFA tests whether data fit a hypothesized, pre-specified factor structure.

What is an eigenvalue in factor analysis, and what is the Kaiser criterion for retaining factors?

An eigenvalue is the amount of total variance explained by a factor; the Kaiser criterion retains factors with eigenvalues greater than 1.0.

Distinguish orthogonal (e.g., Varimax) from oblique (e.g., Promax) rotation in factor analysis.

Orthogonal rotation assumes factors are uncorrelated (90°); oblique rotation allows factors to correlate, which is more realistic when underlying constructs are related.

What is a factorial experimental design and what unique information does it provide?

A design with two or more independent variables each at multiple levels, studied simultaneously; it reveals both main effects of each IV and interaction effects between them.

Differentiate between-subjects and within-subjects (repeated measures) designs.

Between-subjects: different participants in each condition (no carryover, needs more participants); within-subjects: same participants in all conditions (controls individual differences, but risks order/carryover effects).

What is counterbalancing and which design problem does it control?

Systematically varying the order of conditions across participants to control order effects (practice and fatigue) in within-subjects/repeated-measures designs.

In a pretest-posttest control group design, why is the control group essential?

It provides a baseline to rule out threats to internal validity (maturation, history, testing) so that observed change can be attributed to the treatment rather than extraneous factors.