,TABLE OF CONTENT
Part I: General Concepts & Techniques
Chapter 1: Measurement
Chapter 2: Types of Studies
Chapter 3: Frequency Distributions
Chapter 4: Summary Statistics
Chapter 5: Probability Concepts
Chapter 6: Binomial Probability Distributions
Chapter 7: Normal Probability Distributions
Chapter 8: Introduction to Statistical Inference
Chapter 9: Basics of Hypothesis Testing
Chapter 10: Basics of Confidence Intervals
Part II: Quantitative Response Variable
Chapter 11: Inference About a Mean
Chapter 12: Comparing Independent Means
Chapter 13: Comparing Several Means (One-Way ANOVA)
Chapter 14: Correlation and Regression
Chapter 15: Multiple Linear Regression
Part III: Categorical Response Variable
Chapter 16: Inference About a Proportion
Chapter 17: Comparing Two Proportions
Chapter 18: Cross-Tabulated Counts
Chapter 19: Stratified Two-by-Two Tables
,Chapter 1: Measurement – Test Bank
(Advanced, Applied)
Keywords: Biostatistics, measurement scales, data quality, accuracy,
precision, coding, public health data, calculation, applied
Q1: A public health analyst collected weight measurements from 50
participants to summarize population trends. Which is the most appropriate
first step in biostatistical analysis?
A) Performing a t-test
B) Summarizing data using mean, median, and mode
C) Running a regression model
D) Calculating relative risk
Answer: B
Rationale: Before inferential analysis, data must be summarized to
understand distribution, central tendency, and potential anomalies.
Keywords: summarizing data, descriptive statistics, central tendency
Q2: In a study, participants’ responses on smoking frequency were coded as: 0
= never, 1 = occasionally, 2 = daily. What type of measurement scale is this?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: B
Rationale: The responses have a rank order (never < occasionally < daily), but
the intervals are not necessarily equal.
Keywords: ordinal scale, coding, survey data
Q3: You are entering survey data into a spreadsheet for analysis. Rows
represent participants, and columns represent variables. What is the primary
reason for this organization?
A) To perform regression analysis automatically
B) To structure raw data for statistical analysis
C) To calculate variance without errors
D) To convert ordinal variables to interval scale
,Answer: B
Rationale: Proper organization of rows and columns ensures that each
observation and variable is consistently defined, facilitating analysis.
Keywords: data organization, spreadsheet, dataset
Q4: A dataset contains participants’ blood pressure readings in mmHg. Which
of the following is correct about this variable?
A) Nominal with meaningful zero
B) Interval without a true zero
C) Ratio with a true zero
D) Ordinal with rank order only
Answer: C
Rationale: Blood pressure has equal intervals and a true zero, allowing
meaningful ratio comparisons.
Keywords: ratio scale, continuous variable, measurement
Q5: In a lab study, repeated measurements of glucose levels are consistently
higher than the true concentration. What type of error is this?
A) Random error
B) Systematic error
C) Sampling error
D) Confounding error
Answer: B
Rationale: Systematic error occurs when measurements deviate consistently
from the true value, introducing bias.
Keywords: systematic error, measurement bias, accuracy
Q6: A dataset has some participants missing weight values. Which data quality
component does this issue affect?
A) Accuracy
B) Completeness
C) Reliability
D) Precision
Answer: B
Rationale: Missing values reduce completeness, which can bias results and
limit valid inference.
Keywords: data completeness, missing data, data quality
,Q7: When a dataset shows high variability in repeated measurements around
the true value, this reflects:
A) High accuracy, low precision
B) Low accuracy, high precision
C) Low accuracy, low precision
D) High accuracy, high precision
Answer: C
Rationale: Random variation around an incorrect true value indicates both low
accuracy (systematic error) and low precision (random error).
Keywords: accuracy, precision, random error
Q8: A survey uses yes/no responses coded as 1 and 0. The researcher
calculates the mean of this variable. What does this represent?
A) Standard deviation of responses
B) Proportion of “yes” responses
C) Median response value
D) Z-score for the variable
Answer: B
Rationale: For dichotomous variables coded 0/1, the mean equals the
proportion of 1s (yes).
Keywords: dichotomous variable, proportion, coding
Q9: Which scale is appropriate for temperature measured in Celsius?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: C
Rationale: Celsius is interval scale because differences are meaningful, but
there is no absolute zero (0°C does not indicate absence of temperature).
Keywords: interval scale, continuous variable
Q10: A researcher wants to minimize random measurement error in blood
pressure readings. Which strategy is most appropriate?
A) Increase sample size only
,B) Standardize measurement procedures
C) Ignore variation
D) Transform variables to ordinal scale
Answer: B
Rationale: Standardized procedures reduce variability and improve precision.
Keywords: measurement error, precision, standardization
Q11: In coding survey responses numerically, why is consistency in coding
important?
A) It ensures statistical significance
B) It facilitates accurate analysis and reduces errors
C) It converts ordinal variables to interval
D) It reduces random variation
Answer: B
Rationale: Consistent coding allows software to interpret data correctly,
avoiding misclassification or analytical errors.
Keywords: coding, data management, analysis
Q12: Which of the following is the correct hierarchy of measurement scales
from least to most informative?
A) Ratio < Interval < Ordinal < Nominal
B) Nominal < Ordinal < Interval < Ratio
C) Ordinal < Nominal < Ratio < Interval
D) Interval < Ratio < Nominal < Ordinal
Answer: B
Rationale: Nominal provides least information; ordinal adds rank; interval
adds equal spacing; ratio adds true zero and meaningful ratios.
Keywords: measurement scales, hierarchy
Q13: In a dataset of 200 participants, the researcher notes repeated
inconsistencies in coding responses. What data quality aspect is compromised?
A) Completeness
B) Accuracy
C) Reliability
D) Precision
, Answer: C
Rationale: Reliability refers to consistency in measurements; inconsistent
coding reduces reproducibility.
Keywords: reliability, coding, consistency
Q14: A boxplot is constructed for systolic blood pressure in a sample. What
information does it provide?
A) Only mean and variance
B) Central tendency, variability, and outliers
C) Frequency of each measurement
D) Proportion of participants above a threshold
Answer: B
Rationale: Boxplots show median, quartiles, range, and potential outliers
visually.
Keywords: boxplot, central tendency, variability
Q15: Which of the following best illustrates a nominal variable?
A) Blood type (A, B, AB, O)
B) Pain severity score (0–10)
C) Temperature in Celsius
D) Weight in kg
Answer: A
Rationale: Blood type categories have no inherent order, making them
nominal.
Keywords: nominal, categorical, classification
Q16: During survey data entry, the researcher notices a systematic upward
shift in all glucose measurements. Which principle is violated?
A) Precision
B) Accuracy
C) Completeness
D) Validity
Answer: B
Rationale: Accuracy is compromised if measurements consistently deviate
from the true value.
Keywords: accuracy, systematic error, measurement bias
Part I: General Concepts & Techniques
Chapter 1: Measurement
Chapter 2: Types of Studies
Chapter 3: Frequency Distributions
Chapter 4: Summary Statistics
Chapter 5: Probability Concepts
Chapter 6: Binomial Probability Distributions
Chapter 7: Normal Probability Distributions
Chapter 8: Introduction to Statistical Inference
Chapter 9: Basics of Hypothesis Testing
Chapter 10: Basics of Confidence Intervals
Part II: Quantitative Response Variable
Chapter 11: Inference About a Mean
Chapter 12: Comparing Independent Means
Chapter 13: Comparing Several Means (One-Way ANOVA)
Chapter 14: Correlation and Regression
Chapter 15: Multiple Linear Regression
Part III: Categorical Response Variable
Chapter 16: Inference About a Proportion
Chapter 17: Comparing Two Proportions
Chapter 18: Cross-Tabulated Counts
Chapter 19: Stratified Two-by-Two Tables
,Chapter 1: Measurement – Test Bank
(Advanced, Applied)
Keywords: Biostatistics, measurement scales, data quality, accuracy,
precision, coding, public health data, calculation, applied
Q1: A public health analyst collected weight measurements from 50
participants to summarize population trends. Which is the most appropriate
first step in biostatistical analysis?
A) Performing a t-test
B) Summarizing data using mean, median, and mode
C) Running a regression model
D) Calculating relative risk
Answer: B
Rationale: Before inferential analysis, data must be summarized to
understand distribution, central tendency, and potential anomalies.
Keywords: summarizing data, descriptive statistics, central tendency
Q2: In a study, participants’ responses on smoking frequency were coded as: 0
= never, 1 = occasionally, 2 = daily. What type of measurement scale is this?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: B
Rationale: The responses have a rank order (never < occasionally < daily), but
the intervals are not necessarily equal.
Keywords: ordinal scale, coding, survey data
Q3: You are entering survey data into a spreadsheet for analysis. Rows
represent participants, and columns represent variables. What is the primary
reason for this organization?
A) To perform regression analysis automatically
B) To structure raw data for statistical analysis
C) To calculate variance without errors
D) To convert ordinal variables to interval scale
,Answer: B
Rationale: Proper organization of rows and columns ensures that each
observation and variable is consistently defined, facilitating analysis.
Keywords: data organization, spreadsheet, dataset
Q4: A dataset contains participants’ blood pressure readings in mmHg. Which
of the following is correct about this variable?
A) Nominal with meaningful zero
B) Interval without a true zero
C) Ratio with a true zero
D) Ordinal with rank order only
Answer: C
Rationale: Blood pressure has equal intervals and a true zero, allowing
meaningful ratio comparisons.
Keywords: ratio scale, continuous variable, measurement
Q5: In a lab study, repeated measurements of glucose levels are consistently
higher than the true concentration. What type of error is this?
A) Random error
B) Systematic error
C) Sampling error
D) Confounding error
Answer: B
Rationale: Systematic error occurs when measurements deviate consistently
from the true value, introducing bias.
Keywords: systematic error, measurement bias, accuracy
Q6: A dataset has some participants missing weight values. Which data quality
component does this issue affect?
A) Accuracy
B) Completeness
C) Reliability
D) Precision
Answer: B
Rationale: Missing values reduce completeness, which can bias results and
limit valid inference.
Keywords: data completeness, missing data, data quality
,Q7: When a dataset shows high variability in repeated measurements around
the true value, this reflects:
A) High accuracy, low precision
B) Low accuracy, high precision
C) Low accuracy, low precision
D) High accuracy, high precision
Answer: C
Rationale: Random variation around an incorrect true value indicates both low
accuracy (systematic error) and low precision (random error).
Keywords: accuracy, precision, random error
Q8: A survey uses yes/no responses coded as 1 and 0. The researcher
calculates the mean of this variable. What does this represent?
A) Standard deviation of responses
B) Proportion of “yes” responses
C) Median response value
D) Z-score for the variable
Answer: B
Rationale: For dichotomous variables coded 0/1, the mean equals the
proportion of 1s (yes).
Keywords: dichotomous variable, proportion, coding
Q9: Which scale is appropriate for temperature measured in Celsius?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: C
Rationale: Celsius is interval scale because differences are meaningful, but
there is no absolute zero (0°C does not indicate absence of temperature).
Keywords: interval scale, continuous variable
Q10: A researcher wants to minimize random measurement error in blood
pressure readings. Which strategy is most appropriate?
A) Increase sample size only
,B) Standardize measurement procedures
C) Ignore variation
D) Transform variables to ordinal scale
Answer: B
Rationale: Standardized procedures reduce variability and improve precision.
Keywords: measurement error, precision, standardization
Q11: In coding survey responses numerically, why is consistency in coding
important?
A) It ensures statistical significance
B) It facilitates accurate analysis and reduces errors
C) It converts ordinal variables to interval
D) It reduces random variation
Answer: B
Rationale: Consistent coding allows software to interpret data correctly,
avoiding misclassification or analytical errors.
Keywords: coding, data management, analysis
Q12: Which of the following is the correct hierarchy of measurement scales
from least to most informative?
A) Ratio < Interval < Ordinal < Nominal
B) Nominal < Ordinal < Interval < Ratio
C) Ordinal < Nominal < Ratio < Interval
D) Interval < Ratio < Nominal < Ordinal
Answer: B
Rationale: Nominal provides least information; ordinal adds rank; interval
adds equal spacing; ratio adds true zero and meaningful ratios.
Keywords: measurement scales, hierarchy
Q13: In a dataset of 200 participants, the researcher notes repeated
inconsistencies in coding responses. What data quality aspect is compromised?
A) Completeness
B) Accuracy
C) Reliability
D) Precision
, Answer: C
Rationale: Reliability refers to consistency in measurements; inconsistent
coding reduces reproducibility.
Keywords: reliability, coding, consistency
Q14: A boxplot is constructed for systolic blood pressure in a sample. What
information does it provide?
A) Only mean and variance
B) Central tendency, variability, and outliers
C) Frequency of each measurement
D) Proportion of participants above a threshold
Answer: B
Rationale: Boxplots show median, quartiles, range, and potential outliers
visually.
Keywords: boxplot, central tendency, variability
Q15: Which of the following best illustrates a nominal variable?
A) Blood type (A, B, AB, O)
B) Pain severity score (0–10)
C) Temperature in Celsius
D) Weight in kg
Answer: A
Rationale: Blood type categories have no inherent order, making them
nominal.
Keywords: nominal, categorical, classification
Q16: During survey data entry, the researcher notices a systematic upward
shift in all glucose measurements. Which principle is violated?
A) Precision
B) Accuracy
C) Completeness
D) Validity
Answer: B
Rationale: Accuracy is compromised if measurements consistently deviate
from the true value.
Keywords: accuracy, systematic error, measurement bias
