Introduction to Statistics and Data MCQs 2026

Random sampling helps to

1. Aguarantee sample equals population exactly✓
2. Beliminate the need for any statistics✓
3. Censure every sample statistic equals the parameter✓
4. Dreduce bias and allow probability-based inference✓

A biased sample is one that

1. Aalways a random sample with large n✓
2. Balways identical to the population✓
3. Csystematically over- or under-represents some population groups✓
4. Dalways free of error✓

Non-sampling errors include

1. Aonly natural variation from random sampling✓
2. Bmistakes in measurement, recording and non-response✓
3. Conly the effect of sample size on SE✓
4. Donly standard deviation of the sample✓

Sampling error is

1. Aalways zero in random samples✓
2. Bthe same as a transcription mistake✓
3. Conly non-existent in a census✓
4. Dthe difference between a sample statistic and the population parameter due to using a sample✓

Official statistics are typically produced by

1. Aonly private bloggers✓
2. Bonly individual students✓
3. Cgovernment statistical agencies✓
4. Donly fiction writers✓

A statistical survey aims to

1. Aeliminate all sampling error by definition✓
2. Bcollect data from units to learn about a population✓
3. Cavoid any planning or design✓
4. Dignore non-response completely✓

Biostatistics applies statistical methods to

1. Aonly stock market prices✓
2. Bbiological and medical data✓
3. Conly geological maps only✓
4. Donly architectural drawings✓

Applied statistics focuses on

1. Aonly proving mathematical theorems without data✓
2. Bonly defining scales without application✓
3. Conly historical dates of statisticians✓
4. Dusing statistical methods to solve real-world problems✓

Statistical inference requires

1. Aprobability theory and sampling concepts✓
2. Bonly drawing bar charts✓
3. Conly listing data in ascending order✓
4. Donly computing range without context✓

Raw data are

1. Aunorganized original observations as collected✓
2. Balways presented in pie charts✓
3. Calways summarized by mean and SD only✓
4. Dalways adjusted for inflation✓

A variable is

1. Aalways fixed for every observation✓
2. Bonly a population parameter✓
3. Ca characteristic that varies from one unit to another✓
4. Donly a type of graph✓

A constant is

1. Aalways a random variable✓
2. Balways a sample statistic✓
3. Calways a measure of spread✓
4. Da characteristic that does not vary across units in a given study✓

Which variable is measured on an interval scale

1. ABlood type✓
2. BCalendar year of birth✓
3. COrder of finishing a race✓
4. DNumber of siblings✓

Which variable is measured on a ratio scale

1. ATemperature in Celsius✓
2. BDistance travelled in kilometres✓
3. CRank of a student in class✓
4. DType of employment✓

The ratio scale has

1. Aequal intervals and a true zero indicating absence of the quantity✓
2. Bno fixed order among categories✓
3. Cranks without equal spacing✓
4. Dintervals without a meaningful zero✓

The interval scale has

1. Aequal intervals between values but no true zero point✓
2. Bonly unordered categories✓
3. Conly ranks without measurable gaps✓
4. Da true zero meaning absence of the quantity✓

The ordinal scale provides

1. Acategories with no order at all✓
2. Bequal intervals and a true zero point✓
3. Cranked categories where order matters but intervals are not fixed✓
4. Donly ratios of magnitudes✓

The nominal scale of measurement classifies data into

1. Aordered ranks without fixed intervals✓
2. Bcategories with no inherent order✓
3. Cintervals with equal gaps but no true zero✓
4. Dratios with a meaningful zero✓

Continuous data can take

1. Aonly whole numbers✓
2. Bonly ranked categories✓
3. Conly yes/no responses✓
4. Dany value within an interval✓

Discrete data can take

1. Aany value within an interval including fractions✓
2. Bonly qualitative categories✓
3. Conly countable distinct values, often integers✓
4. Donly probabilities between 0 and 1✓

Quantitative data are

1. Aonly nominal labels without order✓
2. Bonly opinions recorded as text✓
3. Cnumerical measurements or counts✓
4. Donly pictures without numbers✓

Qualitative data describe

1. Aonly continuous measurements with decimals✓
2. Bonly ratios of two positive quantities✓
3. Conly frequencies of exactly equal intervals✓
4. Dattributes or categories that cannot be measured on a numerical scale✓

Secondary data are

1. Aalways collected through personal interviews only✓
2. Balways more accurate than primary data✓
3. Cdata already collected by someone else for another purpose✓
4. Donly obtained by laboratory experiments✓

Primary data are

1. Ataken from published reports compiled earlier✓
2. Balways more unreliable than secondary data✓
3. Conly qualitative with no numbers✓
4. Dcollected firsthand for the specific purpose at hand✓

Census data means

1. Ainformation from a random sample only✓
2. Bdata with missing values only✓
3. Cdata arranged in a frequency polygon only✓
4. Dinformation collected from every member of the population✓

A parameter is

1. Aa numerical characteristic of a population✓
2. Ba numerical characteristic of a sample only✓
3. Conly a graph type✓
4. Donly a unit of measurement✓

A sample is

1. Aa subset of the population selected for study✓
2. Bthe entire population always✓
3. Conly the mode of the data✓
4. Donly theoretical assumptions✓

A population in statistics refers to

1. Aonly a small portion selected for convenience✓
2. Bthe complete set of individuals or items under study✓
3. Conly the arithmetic mean of observations✓
4. Donly the largest value in a dataset✓

Inferential statistics deals with

1. Aonly arranging raw data in tables✓
2. Bonly computing the mean of a complete census✓
3. Conly labeling variables without analysis✓
4. Dmaking generalizations about a population based on sample data✓

Descriptive statistics deals with

1. Asummarizing and describing data that have already been collected✓
2. Bdrawing conclusions about a population from a sample only✓
3. Ctesting hypotheses about unknown populations only✓
4. Ddesigning experiments without summarizing data✓

The word statistics is derived from the Latin word

1. Astature meaning height✓
2. Bstatus meaning state✓
3. Cstation meaning place✓
4. Dstatic meaning fixed✓

Statistics is best defined as the science of

1. Acollecting, organizing, presenting, analyzing and interpreting data✓
2. Bonly guessing future events without data✓
3. Conly drawing pictures without numbers✓
4. Donly recording opinions without measurement✓

A statistic is

1. Aalways equal to the population parameter✓
2. Ba numerical measure computed from sample data✓
3. Conly a type of graph✓
4. Donly a scale of measurement✓

In PPSC/FPSC exams, statistics questions often test

1. Abasic definitions, scales and population-sample distinction✓
2. Bonly advanced stochastic calculus✓
3. Conly computer programming syntax✓
4. Donly organic chemistry reactions✓

The scope of statistics includes

1. Aonly multiplication tables✓
2. Bonly drawing maps without numbers✓
3. Cdesign of studies, analysis and interpretation of uncertainty✓
4. Donly legal drafting✓

Multivariate data involve

1. Aonly one variable per unit✓
2. Bonly graphical presentation without numbers✓
3. Cmore than one variable measured on each unit✓
4. Donly population parameters✓

An outlier is

1. Aalways the median value✓
2. Balways the most frequent value✓
3. Calways the population mean✓
4. Dan observation unusually far from the rest of the data✓

Statistics is divided into two main branches

1. Amicro and macro only✓
2. Balgebra and geometry only✓
3. Cdescriptive and inferential statistics✓
4. Ddeductive and inductive logic only✓

Time series data are

1. Acollected from different subjects at one instant only✓
2. Bobservations recorded over successive time periods✓
3. Calways qualitative nominal data✓
4. Dalways free of trend✓

Data collected at one point in time are called

1. Across-sectional data✓
2. Btime series data✓
3. Cpanel data with repeated units only✓
4. Donly experimental data✓