Income in Kansas According to a 2018 Money magazine article, the average income in Kansas is $ 53 , 906 . Suppose the standard deviation is $ 3000 and the distribution of income is right-skewed. Repeated random samples of 400 Kansas residents are taken, and the sample mean of incomes is calculated for each sample. a. The population distribution is right-skewed. Will the distribution of sample means be Normal? Why or why not? b. Find and interpret a z -score that corresponds with a sample mean of $ 53 , 906 . c. Would it be unusual to find a sample mean of $ 54 , 500 ? Why or why not?
Income in Kansas According to a 2018 Money magazine article, the average income in Kansas is $ 53 , 906 . Suppose the standard deviation is $ 3000 and the distribution of income is right-skewed. Repeated random samples of 400 Kansas residents are taken, and the sample mean of incomes is calculated for each sample. a. The population distribution is right-skewed. Will the distribution of sample means be Normal? Why or why not? b. Find and interpret a z -score that corresponds with a sample mean of $ 53 , 906 . c. Would it be unusual to find a sample mean of $ 54 , 500 ? Why or why not?
Solution Summary: The author explains that the distribution of sample means is roughly normal. The sample size is 400, which is large enough to apply the central limit theorem.
Income in Kansas According to a 2018 Money magazine article, the average income in Kansas is
$
53
,
906
. Suppose the standard deviation is
$
3000
and the distribution of income is right-skewed. Repeated random samples of 400 Kansas residents are taken, and the sample mean of incomes is calculated for each sample.
a. The population distribution is right-skewed. Will the distribution of sample means be Normal? Why or why not?
b. Find and interpret a
z
-score
that corresponds with a sample mean of
$
53
,
906
.
c. Would it be unusual to find a sample mean of
$
54
,
500
? Why or why not?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
Throughout, A, B, (An, n≥ 1), and (Bn, n≥ 1) are subsets of 2.
1. Show that
AAB (ANB) U (BA) = (AUB) (AB),
Α' Δ Β = Α Δ Β,
{A₁ U A2} A {B₁ U B2) C (A1 A B₁}U{A2 A B2).
16. Show that, if X and Y are independent random variables, such that E|X|< ∞,
and B is an arbitrary Borel set, then
EXI{Y B} = EX P(YE B).
Proposition 1.1 Suppose that X1, X2,... are random variables. The following
quantities are random variables:
(a) max{X1, X2) and min(X1, X2);
(b) sup, Xn and inf, Xn;
(c) lim sup∞ X
and lim inf∞ Xn-
(d) If Xn(w) converges for (almost) every w as n→ ∞, then lim-
random variable.
→ Xn is a
Chapter 9 Solutions
Pearson eText Introductory Statistics: Exploring the World Through Data -- Instant Access (Pearson+)
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