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Lift Lines and Snowfall: Sample Estimates

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Lift Lines and Snowfall: Sample Estimates

Use random samples to estimate population values and compare how estimates vary.

1. Estimate Lift-Line Waits

Use the random sample to make estimates. Treat each recorded lift-line wait as one observation.

A ski resort recorded 1,200 lift-line waits on Saturday. Priya randomly selected 40 of those records. The table shows all 40 sampled waits.
Random Sample of Saturday Waits
Wait (minutes)Number of records
24
48
614
810
104
1.

What percent of the sampled waits lasted at least 8 minutes? %

2.

Use the sample to estimate how many of Saturday's 1,200 waits lasted at least 8 minutes. waits

3.

Find the mean wait in the sample. minutes

4.
How should the resort use the sample mean when describing all 1,200 recorded waits?
Question 4 options

2. Compare Lift-Line Estimates

Each sample below was selected separately at random from the same 1,200 Saturday records. Records may appear in more than one sample.

Four Random Samples
SampleRecords sampledWaits of 8+ minutes
Pine4012
Summit4018
Ridge4014
Basin4016
5.

Estimate the number of waits lasting at least 8 minutes among all 1,200 records using each named sample. Pine: waits; Summit: waits

6.

Use all four samples to make four population-count estimates. What is the difference between the highest and lowest estimates? waits

7.
The resort averages the four sample percentages to create one planning estimate.

Using that average percentage, how many of the 1,200 waits are estimated to last at least 8 minutes? waits

8.
Why can these four random samples produce different estimates?
Question 8 options
9.
The manager will review staffing if any sample-based estimate exceeds 500 waits lasting at least 8 minutes. Which statement correctly applies this rule?
Question 9 options

3. Compare Snowfall Samples

Use the historical records described below. A sample-based estimate is not an exact count or a forecast.

Mateo studies the resort's daily snowfall records for all 120 days of last season. He selects four separate random samples of 12 days each.
Samples of Last Season's Snowfall
SampleDays sampledDays with 10+ cm
One123
Two125
Three124
Four126
10.

Using Sample One, estimate how many of last season's 120 days had at least 10 cm of snowfall. days

11.

Calculate the percent of days with at least 10 cm of snowfall in each sample. What is the difference between the highest and lowest percentages? percentage points

12.
Mateo also takes four random samples of 24 days each from the same season. Compare the variation in the sample percentages in the two sets. Use the difference between the highest and lowest percentages.
Larger Snowfall Samples
SampleDays sampledDays with 10+ cm
North248
South249
East2410
West249
Question 12 options
13.
The four 24-day samples have an average of 9 days with at least 10 cm of snowfall per sample. Which inference is supported?
Question 13 options
14.
The four 12-day samples give population estimates from 30 to 60 days with at least 10 cm of snowfall. Mateo says, “The actual count must be between 30 and 60 because all four samples were random.” Is that guaranteed? Explain your reasoning.