BUS441 Web Analytics Week 11 Quiz

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Questions and Answers

What distinguishes revenue from being a continuous variable?

It can only take integer values.

It is always reported as a discrete count.

It can take any value within a range. (correct)

It represents the total sum of transactions.

How is conversion rate calculated?

Total revenue divided by the number of transactions.

Count of all transactions divided by pageviews.

Number of successful transactions divided by total site visits.

Count of all users who qualified for a condition divided by total users. (correct)

What type of variable are transactions considered?

Continuous and can take fractional orders.

Neither continuous nor discrete.

Only continuous since they can vary in dollar amount.

Discrete since they can only take whole number values. (correct)

Which of the following is NOT a metric discussed for evaluating data patterns?

Count of total pageviews. Signup and view all the answers

Which element is included in the dimensions and metrics within GA4 reporting?

Traffic segments such as device types. Signup and view all the answers

What is the effect of increasing the sample size on the standard deviation?

It causes the standard deviation to shrink. Signup and view all the answers

Which of the following represents a discrete metric?

Total number of transactions. Signup and view all the answers

What is a key characteristic of continuous metrics?

They can take on an infinite range of values. Signup and view all the answers

What is the consequence of the peaking problem in statistical reporting?

It leads to overconfidence in results. Signup and view all the answers

Which method should be considered to convert a continuous metric into a discrete one?

Count occurrences above or below specific thresholds. Signup and view all the answers

What does a p-value represent in hypothesis testing?

The probability of observing results as extreme as the ones you got, assuming the null hypothesis is true Signup and view all the answers

In which scenario would you typically apply a binomial metric?

Documenting whether a user clicked a button. Signup and view all the answers

Which statement accurately describes a confidence interval?

It is a range that indicates how precise a measurement is Signup and view all the answers

When should you conduct a one-tailed test?

When you expect a specific direction of the effect Signup and view all the answers

When analyzing conversion rates, what does a lift indicate?

An improvement in performance compared to a control group. Signup and view all the answers

What is a Type I error in hypothesis testing?

Declaring the variant a winner when it is not Signup and view all the answers

What does increasing the sample size help to reduce in statistical analysis?

Variability in results. Signup and view all the answers

What is the relationship between Type I and Type II errors?

They are inversely related Signup and view all the answers

What is the best way to reduce the risk of Type I and Type II errors during experiments?

Increase the sample size Signup and view all the answers

In the initial observation of an experiment, what could an unexpectedly high conversion rate suggest?

The results may be a false positive and further testing is needed Signup and view all the answers

What is primarily the purpose of conducting two-tailed experiments?

To assess whether any significant difference exists Signup and view all the answers

What characterizes the variation in Day 2 observation regarding conversions and conversion rates?

Equal conversion rates between control and variation Signup and view all the answers

What was the conversion rate for the control group on Day 3?

53.33% Signup and view all the answers

What conclusion can be drawn from the data collected on Day 4 about the variation?

The variation's conversion rate was lower than the control group's. Signup and view all the answers

What effect did the results from Day 3 have on the perception of the change?

Frustration, suggesting immediate test termination Signup and view all the answers

What is indicated by the 'Lift' percentage when comparing variation to control on Day 5?

The variation performed worse but is still acceptable. Signup and view all the answers

How does collecting more data impact the confidence interval?

It narrows the confidence interval. Signup and view all the answers

What does a conversion rate of 44.00% on Day 5 suggest about the variation’s performance?

It indicates failure compared to higher past rates. Signup and view all the answers

Study Notes

Course Information

Course name: BUS441 Web Analytics
Week: 11
Topic: Experiment Analysis & Interpretation
Term: Fall 2024
Institution: SFU

Disclaimer

Instructor is not a statistician

Traditional Hypothesis Testing

A 6-step "validate" phase for testing hypotheses
Step 1: Formulate the null and alternative hypotheses (H₀ and H₁)
Step 2: Select an appropriate statistical test.
Step 3: Determine the significance level (α).
Step 4: Collect data and calculate the test statistic.
Step 5: Determine the critical value of the test statistic.
Step 6: Compare the probability with the significance level.
Step 7: Reject or do not reject the null hypothesis.
Step 8: Draw a marketing research conclusion

P-values

P-values represent the probability of obtaining results as extreme or more extreme than observed, given that the null hypothesis is true.
Difficulty in explaining p-values intuitively
Understanding involves nuance and complexity.
Intuitive simplification loses details and can lead to misunderstandings.

Confidence Intervals

A confidence interval is a range around a measurement which communicates its precision.
95% confidence interval: For 100 samples using the same plan, 95 of the confidence intervals will contain the true value (estimated from the sample)
Wider confidence interval means reduced precision

One vs. Two-Tailed Tests

One-tailed tests: Suitable for situations with a directional hunch.
Two-tailed tests: More commonly used for determining if a difference exists without a prior directional assumption.
Two-tailed tests are a better default.

Type I and Type II Errors

Type I Error (False Positive): Declaring a variant a winner when it is not.
Type II Error (False Negative): Declaring a winner as no better than the original alternative
Errors inversely related - reducing one often increases the other.

Increasing Sample Size

Crucial for reducing sampling errors.
A larger sample size leads to a narrower confidence interval and greater precision.
Insufficient sample size can lead to inaccurate conclusions.
Statistical significance increases with greater sample amounts.

Bayesian vs Frequentist

Frequentist: use a pre-set significance rate, longer tests with lower intuitive results.
Bayesian: flexible testing times, higher intuitive results, but more complex calculations.

Combination Approach

Stats Engine: statistical significance increases over time. Sequential tests become more confident with each visitor.
Traditional statistics: peeking at results increases the chance of finding significant results which are not actually significant.

Continuous vs Discrete Metrics

Continuous: infinite range of values. (e.g., revenue, transaction value)
Discrete: defined set of possible outcomes (e.g., purchases, page visits)
Continuous metrics can be converted to discrete metrics using thresholds.

Reports in GA4

Real-time reporting
Explore tab versus reports
Dimensions & Metrics
Segments
Traffic from test
Traffic from different sources
Device types
Click data
Pageview data
Data scopes in demo store
Orders & pages
Orders from homepage
Unique orders

Weekly Assignment

AB test results interpretation in Canvas

Up Next

No class next week (Flex) week
Final presentations in 2 weeks
Final exam in ~4 weeks

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Description

This quiz focuses on Experiment Analysis and Interpretation in Web Analytics for Week 11 of BUS441. Students will explore traditional hypothesis testing, including formulating hypotheses, selecting statistical tests, and understanding p-values. Dive into the nuances of analyzing data to make informed marketing conclusions.