Describe the behavior of the function p around its vertical asymptote at x = -9
1 answer:
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Answer:
The correct option is the first graph (Yes)
Step-by-step explanation:
The given function is W(d) = 930/d
Where;
W(d) = The number of days it would take to get to Washington
d = The distance travelled each day in miles
We note that the given graphs have number of days in the y-axis and the miles in the x-axis, and that in the function, the distance Crystal travels each day is constant, <em>d</em>, while the 930 is the total distance from California to Washington, while W(d) is the time
Therefore, the variables for crystal are W(d) and the part of 930 miles completed, while the constant is the speed, d = miles/day, which gives;
W(d) = 930/d
W(d) ∝ Part of 930 miles completed × Constant
∴ W(d) which is the time is directly proportional to the distance
The graph which represents the number of days, W(d) it will take Crystal to get to Washington (miles completed) as a function of distance traveled per day, <em>d</em>, which is constant is a straight line graph which is the first graph
Answer:
a) 0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.
b) 0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
When the distribution is normal, we use the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this question, we have that:
a. What is the probability that the sample mean will be within +/- 5 of the population mean (to 4 decimals)?
This is the pvalue of Z when X = 200 + 5 = 205 subtracted by the pvalue of Z when X = 200 - 5 = 195.
Due to the Central Limit Theorem, Z is:
X = 205
has a pvalue of 0.8413.
X = 195
has a pvalue of 0.1587.
0.8413 - 0.1587 = 0.6426
0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.
b. What is the probability that the sample mean will be within +/- 10 of the population mean (to 4 decimals)?
This is the pvalue of Z when X = 210 subtracted by the pvalue of Z when X = 190.
X = 210
has a pvalue of 0.9772.
X = 195
has a pvalue of 0.0228.
0.9772 - 0.0228 = 0.9544
0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.