Podcast
Questions and Answers
What factors should be considered when predicting if a person will buy a product?
What factors should be considered when predicting if a person will buy a product?
Which combination of factors is MOST likely to influence a purchase according to this model?
Which combination of factors is MOST likely to influence a purchase according to this model?
What is one possible outcome of applying a Naive Bayes Classifier to this dataset?
What is one possible outcome of applying a Naive Bayes Classifier to this dataset?
If a customer buys a product, which scenario might suggest they were influenced by free shipping?
If a customer buys a product, which scenario might suggest they were influenced by free shipping?
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Which of the following would potentially indicate that discounts are effectively influencing purchases?
Which of the following would potentially indicate that discounts are effectively influencing purchases?
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The YardStudio store is unsure about their discount strategies.
The YardStudio store is unsure about their discount strategies.
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The dataset for prediction contains information about customer preferences such as free shipping.
The dataset for prediction contains information about customer preferences such as free shipping.
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The Naive Bayes Classifier is used to predict the likelihood of a customer purchasing a product based only on the day of the week.
The Naive Bayes Classifier is used to predict the likelihood of a customer purchasing a product based only on the day of the week.
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The store's customer dataset consists of 50 days with their statistics.
The store's customer dataset consists of 50 days with their statistics.
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A 'yes' for discount and 'no' for free shipping will always guarantee a purchase.
A 'yes' for discount and 'no' for free shipping will always guarantee a purchase.
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Study Notes
Test Cases for Predicting Purchases at YardStudio
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Dataset 1:
- Day of the week: Monday
- Discount: Yes
- Free shipping: Yes
- Purchase: Yes (Expected result)
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Dataset 2:
- Day of the week: Saturday
- Discount: No
- Free shipping: No
- Purchase: No (Expected result)
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Dataset 3:
- Day of the week: Wednesday
- Discount: Yes
- Free shipping: No
- Purchase: Yes (Expected result)
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Dataset 4:
- Day of the week: Sunday
- Discount: No
- Free shipping: Yes
- Purchase: Yes (Expected result)
-
Dataset 5:
- Day of the week: Friday
- Discount: Yes
- Free shipping: Yes
- Purchase: Yes (Expected result)
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Dataset 6: (Borderline case)
- Day of the week: Tuesday
- Discount: No
- Free shipping: No
- Purchase: Maybe (Expected result: Needs more data for definite result)
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Dataset 7: (Extreme case)
- Day of the week: Friday
- Discount: Yes and extremely high
- Free shipping: Yes
- Purchase: Yes (Expected result)
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Dataset 8: (Extreme case)
- Day of the week: Monday
- Discount: No
- Free shipping: No
- Purchase: No (Expected result)
-
Dataset 9:
- Day of the week: Thursday
- Discount: Yes
- Free shipping: Yes
- Purchase: Yes (Expected result)
-
Dataset 10:
- Day of the week: Sunday
- Discount: Yes
- Free shipping: No
- Purchase: Maybe (Expected Result: Needs more data)
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Dataset 11:
- Day of the week: Monday
- Discount: No
- Free shipping: Yes
- Purchase: Yes (Expected result)
-
Dataset 12: Considering a weekend with different discounts on specific products that day
- Day of the week: Saturday
- Discount: Yes
- Free shipping: No
- Purchase: Yes (Expected Result)
-
Dataset 13: Considering a workday with a weekday deal
- Day of the week: Tuesday
- Discount: Yes
- Free shipping: No
- Purchase: Yes (Expected result)
-
Dataset 14: Considering a holiday with free shipping
- Day of the week: Monday
- Discount: No
- Free shipping: Yes
- Purchase: Yes (Expected result)
-
Dataset 15: Considering a common day with no discount or free shipping
- Day of the week: Wednesday
- Discount: No
- Free shipping: No
- Purchase: No (Expected result)
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Dataset 16: Considering a special day with a free shipping offer that doesn't attract a purchase.
- Day of the week: Friday
- Discount: No
- Free shipping: Yes
- Purchase: No (Expected result)
-
Dataset 17: Data set with mixed day of the week, discount and no free shipping
- Day of the week: Saturday
- Discount: No
- Free shipping: No
- Purchase: No (Expected result)
-
Dataset 18: Data with a very large discount on a specific day, but not free shipping
- Day of the week: Thursday
- Discount: Yes
- Free shipping: No
- Purchase: Yes (Expected result)
-
Dataset 19: Data with discounts only on weekdays
- Day of the week: Friday
- Discount: Yes
- Free shipping: Yes
- Purchase: Yes (Expected result)
-
Dataset 20: Data on a day where there is no offer
- Day of the week: Sunday
- Discount: No
- Free shipping: No
- Purchase: No (Expected result)
Note:
- "Maybe" or "Uncertain" results indicate the need for more data points for specific combinations of input features to refine predictions. Naive Bayes Classifier often works best with plentiful data.
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Description
Test your knowledge on predicting customer purchases based on various factors such as discounts and free shipping. This quiz includes different datasets to illustrate how these factors influence purchasing behavior. Analyze the data and determine expected purchasing outcomes.
