Answer:
See Explanation
Step-by-step explanation:
According to the Question,
- Given That, As part of a quality control process for computer chips, an engineer at a factory randomly samples 212 chips during a week of production to test the current rate of chips with severe defects. She finds that 27 of the chips are defective.
(a) The sample is from all computer chips manufactured at the factory during the week of production. We might be tempted to generalize the population to represent all weeks, but we should exercise caution here since the rate of defects may change over time.
(b) The fraction of computer chips manufactured at the factory during the week of production that had defects.
(c) Estimate the parameter using the data: phat = 27/212 = 0.127.
(d) Standard error (or SE).
(e) Compute the SE using phat = 0.127 in place of p:
SE ≈ √(phat(1−phat)/n) = 0.023.
(f) The standard error is the standard deviation of phat. A value of 0.10 would be about one standard error away from the observed value, which would not represent a very uncommon deviation. (Usually beyond about 2 standard errors is a good rule of thumb.) The engineer should not be surprised.
(g) Recomputed standard error using p = 0.1: SE = 0.021. This value isn't very different, which is typical when the standard error is computed using relatively similar proportions (and even sometimes when those proportions are quite different!).
Answer:
x= 5/8
Step-by-step explanation:
Answer:
Writing it in matrix form
- 2 - 4 - 5 - 155
1 1 6 101
2 2 - 3 37
I hope this helps you
Answer:
c.the area method
Step-by-step explanation:
A scatterplot is a plotting of data that represents the relationship between the two variables that should be numerical in nature. The data points i.e to be shown in a horizontal and vertical axis represent that how much one variable affected by another variable.
In the area method, we plot a data and then draw a shape which can be in oval but it does not include the outliers but the other methods like oval method, divide center method, regression calculator includes the outliers
Therefore the option c is correct
