Market Basket Analysis MCQs

By: Prof. Dr. Fazal Rehman | Last updated: August 7, 2024

1. What is the primary goal of Market Basket Analysis in data mining?
a) To classify customer demographics
b) To identify frequently co-occurring items in transactions
c) To predict future sales trends
d) To cluster similar products together

Answer: b) To identify frequently co-occurring items in transactions

2. Which of the following metrics is commonly used in Market Basket Analysis to measure the frequency of an itemset?
a) Confidence
b) Support
c) Lift
d) Correlation

Answer: b) Support

3. What does the ‘confidence’ metric indicate in Market Basket Analysis?
a) The proportion of transactions that contain a particular itemset
b) The likelihood that a second item is purchased when the first item is purchased
c) The overall frequency of an item in the dataset
d) The strength of an association rule compared to random chance

Answer: b) The likelihood that a second item is purchased when the first item is purchased

4. Which metric in Market Basket Analysis measures the strength of an association rule relative to the co-occurrence of items by chance?
a) Support
b) Confidence
c) Lift
d) Leverage

Answer: c) Lift

5. In Market Basket Analysis, what does a lift value greater than 1 indicate?
a) The items are negatively correlated
b) The items are independent of each other
c) The items are positively correlated
d) The items occur together less frequently than expected by chance

Answer: c) The items are positively correlated

6. Which algorithm is most commonly associated with Market Basket Analysis?
a) K-means
b) Apriori
c) Linear regression
d) Decision trees

Answer: b) Apriori

7. What is the first step in performing Market Basket Analysis using the Apriori algorithm?
a) Generate association rules
b) Calculate lift
c) Find frequent itemsets
d) Sort items by frequency

Answer: c) Find frequent itemsets

8. In the context of Market Basket Analysis, what does the term ‘itemset’ refer to?
a) A single item in a transaction
b) A collection of items that appear together in a transaction
c) A category of similar items
d) A list of transactions

Answer: b) A collection of items that appear together in a transaction

9. Which of the following is NOT a typical application of Market Basket Analysis?
a) Recommending products to customers
b) Optimizing store layouts
c) Detecting fraudulent transactions
d) Identifying frequent item combinations

Answer: c) Detecting fraudulent transactions

10. What is a potential challenge when conducting Market Basket Analysis on large datasets?
a) High computational complexity
b) Lack of interpretability
c) Insufficient data
d) Difficulty in defining itemsets

Answer: a) High computational complexity

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