Well I am not good with ratios but I could try. What do you need help with?
Answer:
no not that wuch
Step-by-step explanation:
Answer:
Type I: 1.9%, Type II: 1.6%
Step-by-step explanation:
given null hypothesis
H0=the individual has not taken steroids.
type 1 error-falsely rejecting the null hypothesis
⇒ actually the null hypothesis is true⇒the individual has not taken steroids.
but we rejected it ⇒our prediction is the individual has taken steroids.
typr II error- not rejecting null hypothesis when it has to be rejected
⇒actually null hypothesis is false ⇒the individual has taken steroids.
but we didnt reject⇒the individual has not taken steroids.
let us denote
the individual has taken steroids by 1
the individual has not taken steroids.by 0
predicted
1 0
actual 1 98.4% 1.6%
0 1.9% 98.1%
so for type 1 error
actual-0
predicted-1
therefore from above table we can see that probability of Type I error is 1.9%=0.019
so for type II error
actual-1
predicted-0
therefore from above table we can see that probability of Type I error is 1.6%=0.016
Answer:
Mean: 16.75
Median: 15.5
Mode: 13
Range: 16
Minimum: 9
Maximum: 25
Count n: 16
Sum: 268
Step-by-step explanation:
hope this helps!
Answer:Team C
Step-by-step explanation: By looking at the graph i can tell that team c has more dots on the larger side of the line.
