Answer:
We want to reduce type II error we carry out the test using a larger significance level (such as 0.10) and not a small significance level α (such as 0.01).
Step-by-step explanation:
Type I error
- Rejecting the null hypothesis when it is in fact true is called a Type I error.
- It is denoted by alpha, α that is the significance level.
- Lower values of alpha make it harder to reject the null hypothesis, so choosing lower values for alpha can reduce the probability of a Type I error.
It is given that the consequences of a Type I error are not very serious, but there are serious consequences associated with making a Type II error.
Type II error
- This is the error when we fail to reject a false null hypothesis or accept a null hypothesis when it is true.
- Higher values of alpha makes it easier to reject the null hypothesis.
- So choosing higher values for alpha can reduce the probability of a type II error.
- The consequence here is that if the null hypothesis is true, increasing the value of alpha makes it more likely that we make a Type I error.
Since, we want to reduce type II error we carry out the test using a larger significance level (such as 0.10) and not a small significance level α (such as 0.01).
This will increase type I error but that is okay since we do not have serious consequences for it.
Here is the answer to the question above. If the value of an airplane is depreciating at a rate of 7% per year, and in the year 2004, it was worth 51.5 million, here is the value of the airplane in 2013.
2005 : 47, 895, 000
2006 : 44, 542, 350
2007 : 41, 424, 385.5
2008 : 38, 524, 678.5
2009 : 35, 827, 951
2010 : 33, 319, 994.4
2011 : 30, 987, 594.8
2012 : 28, 818, 463.2
2013 : 26, 801, 170.8
So the value of the airplane in 2013 is $26, 801, 170.8.
Hope this helps.
The answer you would get would be x (-x^2-x+4+7x^4)
Answer:
1.) No
2.) 40 goals
Step-by-step explanation:
Given the following :
Last season:
Games played = 15
Points scored = 41
Current season:
Games played = 9
Points scored = 24
A)
Last season:
Goals per game = total points / number of games
Goals per game = 41 / 15 = 2.733
Current season :
Goals per game = total points / number of games
Goals per game = 24 / 9 = 2.667
Last season's goal per game is greater than that of current season.
B)
Current rate = goals / games = 24/9 - - - (1)
Let points to be scored this season = y
Ratio of y to number of games played last season = y / 15 - - - (2)
Equate both
24 / 9 = y / 15
9 * y = 24 * 15
y = 360 / 9
y = 40
If you use 1 teaspoon of vinegar in 2 teaspoons of mayonnaise divide 16 by 2 and you will have your answer.
