Question Type 1: Given some worded scenario of real-life data collection, outlining the characteristics of the data and possible problems Exercises

A health study uses volunteer participants wearing fitness trackers to record daily steps. Characterize the data, critique the sampling method, and suggest one statistical correction for self‐selection bias.

A market researcher samples weekly grocery expenditure by interviewing customers at one high‐end supermarket. Describe the sampling method, discuss its limitations, and suggest a sampling strategy to reflect citywide spending habits.

A meteorological station records temperature every hour but one sensor is known to read $2^\circ\text{C}$ too low. Classify the error type, discuss its impact on data, and recommend how to adjust recorded values.

A city planner measures average commute times by surveying people waiting at a downtown bus stop at $8\text{ am}$. Outline the data characteristics, evaluate the sampling technique, and propose two ways to reduce bias.

A university collects final exam scores (out of 100) from a single tutorial group to represent the entire course.

State the type of data collected. Discuss the representativeness of the data, identify potential sampling flaws, and recommend an improved sampling design.

(a) State the data type of the variable 'mode of travel'.

(b) Explain one possible source of sampling bias in this survey.

(c) Suggest one alternative sampling method to reduce this bias.

In a rural clinic, blood pressure readings are taken from patients who walk in without appointment. Discuss the sampling frame, identify flaws, and suggest how to estimate true population blood pressure distribution.

Parents report their children’s daily mobile phone usage hours in a school survey. Outline the data type, potential reporting errors, and propose how to validate responses.

Explain the data type, sampling approach, pitfalls, and propose one way to obtain more representative feedback.

A survey of patients in a clinic records pain on a scale of 0–10 but gives no verbal anchors. Describe the scale type, potential measurement issues, and suggest how to improve reliability.

Characterize the data, identify any biases, and recommend one way to capture full sleep patterns.