Annual incomes are known to have a distribution that is skewed to the right instead of being normally distributed. assume that we collect a large (ngreater than30) random sample of annual incomes. can the distribution of incomes in that sample be approximated by a normal distribution because the sample is large? why or why not?

No.

Step-by-step explanation:

According to the central limit theorem,

Then the distribution of sample means can be approximated by a normal distribution. And the mean of this distribution converges true mean of annual incomes.

But distribution of annual incomes inside a sample may not be normal.

the inequality is:

250c+180g≥950

step-by-step explanation:

let c denotes the number of days in a week   miyoko worked as a cryptographer.

and g denotes the number of days in a week she works as a geologist.

now we are given that she earns $250 for every day she works as a cryptographer,and earns $180 for every day she works as a geologist.

now miyoko's goal is to earn more than $950 this week.

hence, the inequality could be represented as:

250c+180g≥950

x =-.20752

step-by-step explanation:

4^(x+2)=12

4^(x+2)=12

take the log base 4 on each side

log 4 (4^(x+2) = log 4(12)

we know log b(a^y) = y log b (a)

(x+2) log 4(4) = log 4 (12)

x+2 = log 4 (12)

we know   logb c = loga c/loga b

we want to convert to base 10   so a = 10

by default, we do not write the 10   c = 4   and b = 10

log4 10 = log 12/log 4

log4 10 = log 12/ log 4

x+2 = log 12/ log 4

subtract 2 from each side

x +2 -2 = log 12/ log 4 -2

x = 1.79248125 -2

x =-.20752