Answer:
b - 28
Step-by-step explanation:
If she gives away 28 buttons that means she subtracts 28 from the amount she had
b - 28 is what she has left
Answer:
-4 and 0
Step-by-step explanation:
Rise over Run would give us the slope.
In the first graph, It goes down 4 while it goes 1 to the right.
This means that -4/1 = -4.
The second graph does not go up or down, meaning 0, while it goes 1 to the right.
This means that 0/1 = 0.
Answer:
The sample size is 
Step-by-step explanation:
From the we are told that
The population proportion is p = 0.90
The margin of error is E = 0.01
From the question we are told the confidence level is 95% , hence the level of significance is
=> 
Generally the sample size is mathematically represented as
![n =[ \frac{ Z_{\frac{\alpha }{2} } }{E} ]^2 * p(1-p)](https://tex.z-dn.net/?f=n%20%20%3D%5B%20%20%5Cfrac%7B%20Z_%7B%5Cfrac%7B%5Calpha%20%7D%7B2%7D%20%7D%20%20%7D%7BE%7D%20%5D%5E2%20%2A%20p%281-p%29)
=> ![n =[ \frac{ 1.96 }{0.01} ]^2 * 0.90(1-0.90)](https://tex.z-dn.net/?f=n%20%20%3D%5B%20%20%5Cfrac%7B%201.96%20%20%7D%7B0.01%7D%20%5D%5E2%20%2A%200.90%281-0.90%29)
=>
Answer:
a. 250 fields
b. 220 to 280 fields
c. Fields are not independent
Step-by-step explanation:
a. The average number of fields sampled that are infested with whitefly =
number of fields X Percentage sampled, 10%
= 2500 X 10% = 250 fields
b. Going by the binomial distribution is the square of the standard deviation, divided by (the product of the sample size n, and the probability a and b). While the standard deviation is the square root of the variance
σ = √nab
= √na(1-a) = √2500 X 10% X (1- 10%)
= √225 = 15
Now let's use the empirical rule that says about 95% of the observations are within two standard deviations from the mean since the number of trials is very large
μ - 2σ = 250 - 2(15) = 220
μ + 2σ = 250 + 2(15) = 280
Approximately 220 to 280 fields are expected to be infested going by 95% probability observation
c. Since x=25 is considered small and is not captured within 220 and 280 fields making one of the characteristics of binomial experiment not satisfied which expects each field to be independent. Making fields that are close together more likely to be infected.
