Answer:
Step-by-step explanation:
Hello!
The study variable is:
X: number of customers that recognize a new product out of 120.
There are two possible recordable outcomes for this variable, the customer can either "recognize the new product" or " don't recognize the new product". The number of trials is fixed, assuming that each customer is independent of the others and the probability of success is the same for all customers, p= 0.6, then we can say this variable has a binomial distribution.
The sample proportion obtained is:
p'= 54/120= 0.45
Considering that the sample size is large enough (n≥30) you can apply the Central Limit Theorem and approximate the distribution of the sample proportion to normal: p' ≈ N(p;
)
The other conditions for this approximation are also met: (n*p)≥5 and (n*q)≥5
The probability of getting the calculated sample proportion, or lower is:
P(X≤0.45)= P(Z≤
)= P(Z≤-3.35)= 0.000
This type of problem is for the sample proportion.
I hope this helps!
Answer:
I would have to say ether between 15 and 45 or 8 and 24, if it's not that then I got nothing.
Answer:
The points are randomly scattered with no clear pattern
The number of points is equal to those in the scatterplot.
Step-by-step explanation:
The points in the residual plot of the line of best fit that is a good model for a scatterplot are randomly scattered with no clear pattern (like a line or a curve).
The number of points in the residual plot is always equal to those in the scatterplot.
It doesn't matter if there are about the same number of points above the x-axis as below it, in the residual plot.
The y-coordinates of the points are not the same as the points in the scatterplot.
Answer:
1/4
Step-by-step explanation:
15 out of the 20 books are horses. 5 of those are nature. 5/20 is the fraction, but can be simplified to 1/4