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Women’s shoes that are of low quality, on average, will eventually sell at a price that is about 35% of the actual retail price. Shoe companies count on some customers to purchase low quality shoes at a high price. This is known as: _____________________________________________. 

The buying power of the LGBTQ+ community is approaching $1.5 trillion. This demographic is known to be tech savvy, early adopters, brand loyal, and having higher discretionary income. As a key executive with Samsung Electronics (in its U.S. operations), what specific steps will you take to produce new, innovative products to attract this important consumer group?

The ratio of the group’s percentage of the population and their percentage of the total market share or buying power is also known as their: ______________________________.

The “5 Ways Marketers Can Take Action to Improve Diversity” includes: __________________________________________.

In our class, we looked at photos of motorcycles that were designed by women for women. We also watched the video that highlights the feature of the Volvo YCC concept car that was designed by women for women. 

A few rows from a dataset are shown below. Assume that the house_price represents the price in dollars (ignore the fact that these prices are unrealistic in today’s market) | square_feet| house_price|property_type |location_grade | |———–:|———–:|:————-|:————–| | 2282| 2604|Townhome |A | | 1624| 1103|Townhome |C | | 2189| 2670|Condo |C | | 1737| 1747|House |C | | 1905| 2428|House |A | | 1549| 1456|Townhome |A | The standard deviation of the column house_price has units of and it is the of the variance.

A few rows from a dataset are shown below. This dataset shows some company’s expenditure on product promotion in several areas of the country and the corresponding demand for the product. |Product | Expenditure| Demand| |:——-|———–:|——:| |Y | 376| 475| |Y | 412| 589| |X | 144| 532| |X | 220| 521| |X | 166| 591| |Y | 369| 515| For the above, I built a model with Demand as the response variable and Product and Expenditure as the explanatory variables. I got the following model output. |term | .lwr| .coef| .upr| |:———–|————:|———-:|————:| |(Intercept) | 493.0582505| 505.49608| 517.9339017| |Expenditure | 0.4589472| 0.50854| 0.5581328| |ProductY | -220.7083913| -207.51193| -194.3154729| |ProductZ | -430.7360919| -408.91989| -387.1036962|   Based on the above, write out the the model function (round any numbers up to the next higher whole number).

The figure below shows a point plot annotated with a statistical model. The plot also shows the model function. We have referred to this band as the 95% confidence interval. What exactly does this mean?  

If we have two groups of numbers with each having 200 elements and the same average, but different variance, what does it say about the two groups?

The first figure below shows the distribution of annual incomes of people in some country in the form of a continuous probability density function.  The shaded region corresponds to the area under the curve for x values above $24,960 (average income). A label shows the numeric value of this area.The second figure shows the same probability density function, but with the area under the curve for x-values above $15,700 shaded. Using these figures, what is the probability that someone earns between 15700 and 24960? Write in a number between 0 and 1 correct to two decimal places?