Answer:
The linear model will give a good approximation if the new value is within or close to the values we used to construct the linear model.
Step-by-step explanation:
A linear model gives reasonable approximations under these two conditions:
- If the value for which we need to use the approximation is within the range of values we used to construct the linear model
- If the value for which we need to use the approximation is close to the values which we used to construct the linear model.
For the given model, heights of children aged 5 to 9 were recorded. Here, age is the independent variable and height will be the independent variable. Heights of 30 children from age 5 to 9 were recorded and a linear model was constructed. Now, we need to tell which value of age can be made an input of this function to find the approximate height.
Using the above two principles, the linear model will give a good approximate if:
- The age of the child is between 5 and 9 years. In this situation, the value approximated by the model will be closer to the actual height in majority of the cases. For example, the model will give good approximations for children of ages 6, 6.5, 7, 7.75 etc
- The age of child is close to 5 and 9 years old but outside the range. In this case, the model will also give good approximations. For example. for a child of age 4.5 years or 10 years, the model will still give a good and reasonable approximations.
Answer:
7
Step-by-step explanation:
We can check if it works:
7+(-6) is the same as saying 7-6 which is equal to 1. Therefore, we are correct. Hope I could help!
Answer: A: 60, since x = the amount of seconds and the 8 represents the seconds then you'll add 8x+42 and get 60
B: 54, now in this step find what -3x2 is which give you -6 since they're different signs then subtract and your answer will be 54
Step-by-step explanation:
Answer:
Reject <em>H</em>₀ if: or .
Step-by-step explanation:
The hypothesis for the one-tail t-test is:
<em>H</em>₀: The population mean is 100, i.e. <em>μ</em> = 100.
<em>Hₐ</em>: The population mean is less than 100, i.e. <em>μ</em> < 100.
The significance level of the test is, <em>α</em> = 0.05.
The number of observations in the sample is, <em>n</em> = 25.
The degrees of freedom of the test is:
df = n - 1
= 25 - 1
= 24
Compute the critical value of <em>t</em> as follows:
*Use a <em>t</em>-table.
The rejection region can be defined as follows:
Reject <em>H</em>₀ if: or .
Answer:
can u say in english
Step-by-step explanation:
please