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To calculate the expected value for the number of sales generated by the web retargeting strategy for new customers, we can use the formula for expected frequency in a contingency table:

\[
\text{Expected Value} = \frac{(\text{Row Total}) \times (\text{Column Total})}{\text{Grand Total}}
\]

In this case, we are focusing on the "New customer" row and the "Web retargeting" column. From the table, the values are:

- Row Total for new customers: 461
- Column Total for web retargeting: 311
- Grand Total: 919

Now, we can plug these values into the formula:

\[
\text{Expected Value} = \frac{461 \times 311}{919}
\]

Let me calculate that for you.The expected value for the number of sales generated by the web retargeting strategy for new customers is approximately **156.007617** (rounded to six decimal places).

Would you like further details or have any other questions?

Here are 5 related questions to expand your understanding:
1. How do we calculate the expected values for other cells in this contingency table?
2. What is the next step in performing a Chi-Square test of independence?
3. Why is the Chi-Square test appropriate for this type of analysis?
4. How do we interpret the results of the Chi-Square test at different significance levels?
5. What would happen if the significance level were changed to 0.01 instead of 0.005?

**Tip:** When dealing with contingency tables, ensure each expected frequency is sufficiently large (usually ≥ 5) to validate the use of the Chi-Square test.

A marketing firm wants to know if there is a difference in the best marketing strategy for new customers compared to returning customers. Is there sufficient evidence at the 0.005 level of significance to conclude that an association exists between marketing strategy and customer type? Step 1: Calculate the expected value for the number of sales generated by the web retargeting strategy for new customers.

Learn how to calculate the expected values for web retargeting sales in a marketing strategy analysis using a contingency table. The problem includes the use of the Chi-Square Test of Independence to determine if there is an association between marketing strategy and customer type at a 0.005 level of significance.

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