Data Analysis

A retail analyst ran a promotional pricing experiment exclusively at three flagship stores located in affluent urban downtowns. The promotion increased average basket size by 18%, a statistically significant result. Leadership wants to roll the promotion out to all 400 stores nationwide, including rural and suburban locations, and expects the same 18% lift. What is the MOST important validity concern the analyst should raise?

A data analyst at a fitness center reviews a histogram of member visit frequency per month. The histogram shows two distinct peaks — one cluster around 3 visits and another around 20 visits — with relatively few members visiting between 8 and 14 times. What does this pattern most likely indicate, and what should the analyst do?

A retail analyst wants to determine whether a customer's preferred payment method (cash, credit, mobile wallet) is associated with their membership tier (basic, premium). Both variables are categorical, and the analyst has a contingency table of observed counts. Which statistical test is most appropriate to assess whether an association exists between these two variables?

A retail analyst is comparing sales performance across three regional stores that opened in different years and had very different starting revenue levels. Leadership wants to fairly compare how much each store has grown relative to its own opening year, not which store has the highest raw dollar sales. Which analysis technique should the analyst apply to enable this comparison?

A retail analyst wants to determine whether average customer satisfaction scores differ across four different store regions (North, South, East, West). Each region has an independent sample of survey respondents, and the analyst wants to test all four regional means simultaneously in a single test while controlling the overall Type I error rate. Which statistical method is most appropriate?

A retail analyst wants to determine whether the average purchase amount differs between customers who received an email coupon and those who did not. Each group contains about 200 customers, the purchase amounts are roughly normally distributed, and the analyst wants to know if the observed difference in group means is statistically significant. Which statistical method is most appropriate?

A market research analyst reports that the average customer satisfaction score is 7.4 with a 95% confidence interval of 6.1 to 8.7, based on a sample of 40 respondents. The marketing director says the estimate is too imprecise to act on and asks the analyst how to narrow the interval while keeping the 95% confidence level. What is the most appropriate action?

A retail analyst reports that the average monthly customer spend is estimated at $84.50 with a 95% confidence interval of $80.10 to $88.90. A store manager asks what the '95% confidence' actually means for this estimate. Which interpretation should the analyst give?

A retail analyst reports that stores offering free in-store coffee have 30% higher sales than stores without it, concluding that coffee service drives sales. A senior analyst notes that all the coffee-serving stores happen to be located in high-income urban downtown areas, while the non-coffee stores are in low-traffic rural locations. What is the primary threat to the validity of the original conclusion?

A retail analyst has been asked to produce a monthly report that summarizes what happened last quarter: total units sold, average revenue per store, and the percentage change from the previous quarter. The stakeholders explicitly state they only want a clear summary of past performance, not forecasts or explanations of causes. Which type of analysis best fits this request?

A data analyst receives a new dataset of customer order values and has no prior expectations about its structure. Before selecting summary statistics or building any model, the analyst wants to visually understand the shape of the distribution, spot any multiple peaks, and detect potential skew. Which analysis technique and visualization best supports this initial goal?

A quality analyst runs a hypothesis test to determine whether a new packaging process changed the average fill weight of cereal boxes. The null hypothesis states the mean fill weight is unchanged. The analyst sets alpha at 0.05 and, after collecting data, rejects the null hypothesis. Later, an independent audit confirms the process actually did NOT change the mean fill weight. What type of error did the analyst make?

An analyst reviews 15 years of monthly housing-start data for a national homebuilder. She notices that construction activity rises and falls in irregular waves that last between three and six years each, and these swings do not repeat at fixed calendar intervals. Separately, she can see a smaller, consistent dip every December. Management asks her to describe the longer three-to-six-year fluctuation. Which type of pattern is she describing?

A retail analyst plots monthly online sales for the past three years. The scatter plot shows values steadily increasing over time with no repeating peaks and valleys and no sudden level shifts. Before building a forecast, the analyst wants to correctly label the dominant pattern present in the data. Which pattern best describes what the analyst observes?

A retail analyst builds a multiple linear regression model to predict weekly store revenue using two predictors: advertising spend (in dollars) and number of staff on shift. The output shows a coefficient of 4.2 for advertising spend, with all other variables held constant. Which interpretation of this coefficient is correct?

A retail analyst runs a linear regression to test whether an increase in store parking spaces predicts daily foot traffic. The model returns a slope coefficient of 4.2 with a 95% confidence interval of [-1.8, 10.2] and a p-value of 0.14. Management asks whether they can conclude that adding parking spaces increases foot traffic. What is the most accurate interpretation?

A quality analyst runs a hypothesis test to determine whether a new supplier's parts have a different mean tensile strength than the current supplier's parts. Using a significance level of 0.05, the test produces a p-value of 0.18. What is the correct conclusion?

A retail analyst runs a simple linear regression predicting monthly sales from advertising spend. The model reports a slope coefficient with a p-value of 0.002 and an R-squared of 0.18. The marketing director wants to know what these two results together tell them about the relationship. What is the most accurate interpretation?

A retail analyst builds a regression model to predict weekly sales from advertising spend. The model output reports an R-squared of 0.82 and a standard error of the estimate (SEE) of $3,400. A manager asks the analyst what the SEE tells them about the model. Which interpretation is correct?

A retail analyst builds a simple linear regression to predict monthly sales revenue (in dollars) from advertising spend (in dollars). The fitted model is: Revenue = 8,500 + 4.2 × (Ad Spend). Both variables are measured in dollars and the model is statistically significant. How should the analyst interpret the slope coefficient of 4.2?