Let x = the number of penguins we are finding
x ÷ 100 × 30 = 15
x = 15 ÷ 30 × 100
x = 50
hope this helps and have a great day :)
Answer:
The p value for this case would be given by:
Since the p value is higher than the significance level provided we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true mean is not significantly less than 20 ounces.
Step-by-step explanation:
Information provided
represent the sample mean
represent the population deviation
sample size
represent the value that we want to test
represent the significance level
z would represent the statistic
represent the p value
Hypothesis to test
We want to test if the true mean is at least 20 ounces, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
The statistic is given by:
(1)
Replacing the info given we got:
The p value for this case would be given by:
Since the p value is higher than the significance level provided we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true mean is not significantly less than 20 ounces.
Answer:
1.)
≈ 3.652
2.) I would say something about how the A in front of cos in the equation would change to 90, rather than stay 75 (in the equation for the step by step), but it would be easier to just use the Pythagorean theorem.
Step-by-step explanation:
I think we may have the same class so hopefully this helps:
1.)
--> law of cosines formula.
--> plugged in numbers; when you draw the triangle, the included angle would be A, and the opposite side would be a. B and b, and C and c are opposite each other. In this case, a is the hypotenuse.
--> in between steps.
--> more simplifying.
--> answer
2.) This one is just an explanation: The 75 in the equation is the given angle, which is a. If this changes, it would just change in the equation too. And obviously, if it's 90 degrees, you can just use Pythagorean theorem a^2+b^2=c^2.
Good luck! :)
We assume data and prediction as question is incomplete
Answer and Step-by-step explanation:
Least squares regression line equations are used to model the relationship that exists between two variables, dependent and independent variables. The equation has the form y=a+bx where y is the dependent variable and x is independent variable, a is a constant and is the y intercept and b is the slope of the line. This relationship is then used to predict future outcomes.
Given that data for 2004-2005 for the basketball players are :
James- 20 points
John- 30 points
Chris- 50 points
Dave-15 points
Donaldson- 32 points
Richard -40 points
We predict the scores/points for James (for example) for the following year using the equation of the regression line y=0.79x+1544
We substitute his points x=20 I'm the equation:
Y=0.79*20+1544
=1599.8
The predicted value is 1599.8