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Worked solution

Use a frequency list for daily car sales

The table records the number of cars sold per day over 50 days.

Cars sold123456
Days1888574

Find unbiased estimates of the mean and variance of the number of cars sold.

CJC · Lecture · Example 3

Method 1: frequency-weighted totals

n=18+8+8+5+7+4=50n=18+8+8+5+7+4=50, ∑fx=18+16+24+20+35+24=137\sum fx=18+16+24+20+35+24=137 and ∑fx2=18+32+72+80+175+144=521\sum fx^2=18+32+72+80+175+144=521. Thus xˉ=137/50=2.74\bar x=137/50=2.74 cars and s2=149(521−137250)=72812450≈2.97\begin{aligned}&s^2\\ & =\frac1{49}\left(521-\frac{137^2}{50}\right)\\ & =\frac{7281}{2450}\approx2.97\end{aligned} in squared car-count units.

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Method 2: calculator with two lists

Choose STAT → 1:Edit and enter the six car counts in L1, their frequencies in L2. Choose STAT → CALC → 1:1-Var Stats, set List L1 and FreqList L2 using 2nd 2, then Calculate and ENTER. The output is xˉ=2.74\bar x=2.74, ∑x=137\sum x=137, ∑x2=521\sum x^2=521, Sx=1.723901602S_x=1.723901602, σx=1.706575518\sigma_x=1.706575518, n=50n=50, minimum 1 and first quartile 1. Squaring stored SxS_x gives 2.971836735, hence 2.97. The teacher’s point is that L2 supplies counts: there are 50 observations, not six.

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Common mistakes

Leaving FreqList empty treats 1,2,3,4,5,6 as equally frequent. As in Example 2, Sx² estimates variance without bias; Sx itself is not generally an unbiased SD estimate.

Solution notes

Teacher page 12 explicitly highlights the need for L2. Both source methods and every table entry retained. No marks printed.

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