The answer is x = -0.6 and y = -8.2.
<h2>Answer :</h2>
- He need 111.75 minutes to cook the meal
- He need to start at 2.08.15 P.M. in order to complete the cooking at 4 P.M.
<h2>Step-by-step explanation :</h2><h3>
Known :</h3>
- George can only cook one thing at a time
- Turkey takes 90 minutes to cook
- Pumpkin pie takes 20 minutes to cook
- Rolls take 60 seconds to cook
- A cup of coffee takes 45 seconds to heat
<h3>Asked :</h3>
- Time needed to cook the meal
- Time he need to start in order to complete the cooking at 4 P.M.
<h3>Completion :</h3>
Let's convert all the seconds to minutes. We know that 60 seconds is equal to one minute. So,
60 seconds = 1 minutes
45 seconds = 45/60 minutes = 0.75 minutes
Time needed = Turkey + Pumpkin pie + Rolls + Coffee
Time needed = 90 + 20 + 1 + 0.75
Time needed = 111.75 minutes
Then, we'll calculate the time he need to start in order to complete the cooking at 4 P.M. First, let's convert the minutes to clock format.
111.75 minutes = 1 hour and 51.75 minutes
111.75 minutes = 1 hour and 51 minutes and 45 seconds
Lastly, calculate the time he need to start in order to complete the cooking at 4 P.M.
4h 0m 0s - 1h 51m 45s = 2h 8m 15s
<h3>Conclusion :</h3>
- He need 111.75 minutes to cook the meal
- He need to start at 2.08.15 P.M. in order to complete the cooking at 4 P.M.
Answer:
The hot dog are $2.63
Step-by-step explanation:
Hot Dogs = H
Drinks = D
2H + 2D = 4
Divide both sides by 2
H + D = 2
Subtract D from either side
H = 2 -D
3H + D = 4.50
Plug in 2 - D for H
3(2- D ) + D = 4.50
6 - 3D + D = 4.50
6 - 4D = 4.50
Add 6 to either side
-4D = 10.50
Divide either side by -4
D = -2 . 625
Answer:
It mean that the observed progeny is similar than the expected progeny. There is no a relationship between the categorical variables.
Step-by-step explanation:
The Chi-squared test is used to test the relationship between categorical variables. A categorical variable is a non-numerical variable. The null hypothesis of the Chi-squared test is that categorical variables are independent; it means that the frequencies are not dependent on the variable. It is important to know that the Chi-squared test does not measure causality, it only measures the relationship. To reject the null hypothesis, you usually need a probability lower than 0.05, but in this case, the probability was way higher than 0.05, it was between 0.5 and 0.9.