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Statistics for Data Science

Week 1 Practice Quiz - 6 MCQs plus written prompts

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Answer the interactive MCQs below. Your progress saves locally so you can revisit later.

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Section A: Quick Concept Checks

Use these short prompts for rapid recall before attempting the MCQs.

  1. State a one line definition of statistics.
  2. Explain the difference between descriptive and inferential statistics.
  3. Give one example each for a population and a sample.
  4. Describe the difference between a case and a variable.
  5. Distinguish cross sectional and time series data.
  6. List the four scales of measurement.

Section C: Short Answer Practice

  1. If nineteen students are surveyed for marks, what is the sample size?
  2. Between any two rational numbers, how many rational numbers can exist?
  3. Write the reduced form of 18/60.
  4. Label each data source as structured or unstructured:
    • A shopkeeper note with sales written freely.
    • An Excel sheet with student marks.

Section D: Applied Dataset

Use the mini dataset to practice identifying variables and drawing conclusions.

Player Matches Runs Batting average Wickets
Sachin 463 18426 44.8 154
Kohli 254 12040 59.1 4
Dhoni 350 10773 50.6 1
  1. Who has the highest batting average?
  2. Identify one categorical variable in the table.
  3. Would you classify this dataset as descriptive or inferential? Explain briefly.

Answer Key

MCQ Solutions

  • Q1: Option B
  • Q2: Option C
  • Q3: Option A
  • Q4: Option C
  • Q5: Option D
  • Q6: Option B

Written prompts

  • Section A: Refer to Week 1 notes for model explanations.
  • Section C: Answers - (1) 19, (2) Infinitely many, (3) 3/10, (4) Shopkeeper note is unstructured, Excel sheet is structured.
  • Section D: Highest average is Kohli, categorical variable is Player, dataset serves descriptive insight.

Review Every Question

Prefer a single scrolling list? Use this section to skim all six MCQs along with their options.

  1. What is the primary purpose of descriptive statistics?
    • To make predictions about future data
    • To summarise and describe data characteristics
    • To test hypotheses
    • To establish causation
  2. Which of the following is an example of discrete quantitative data?
    • Height of students
    • Weight of objects
    • Number of books in a library
    • Temperature readings
  3. What is the median of the dataset: 3, 7, 2, 9, 5?
    • 5
    • 7
    • 5.2
    • 6
  4. Which measure of central tendency is most affected by outliers?
    • Mode
    • Median
    • Mean
    • All are equally affected
  5. What type of data is "customer satisfaction rating" (Poor, Fair, Good, Excellent)?
    • Nominal
    • Ordinal
    • Discrete quantitative
    • Continuous quantitative
  6. The standard deviation is:
    • The square of variance
    • The square root of variance
    • The same as variance
    • Always larger than variance