Answer:
Below It shows how to cancel it.
Step-by-step explanation:
Answer:
We conclude that the calibration point is set too high.
Step-by-step explanation:
We are given the following in the question:
Population mean, μ = 1000 grams
Sample mean, 
= 1001.1 grams
Sample size, n = 50
Alpha, α = 0.05
Population standard deviation, σ = 2.8 grams
First, we design the null and the alternate hypothesis
We use One-tailed(right) z test to perform this hypothesis.
Formula:
Putting all the values, we have
Now, 
Since,
We reject the null hypothesis and accept the alternate hypothesis. We accept the alternate hypothesis. We conclude that the calibration point is set too high.
Answer:
what grade are u in and what are the answer choices if the steps are the choices then try step 3
Step-by-step explanation:
Answer:
That would be sina.
Step-by-step explanation:
sin(a+b) = sinacosb + cosasinb
sin(a-b) = sinacosb - cosasinb
Adding we get sin(a+b) + sin(a-b) = 2sinaccosb
so sinacosb = 1/2sin(a+b) + sin(a-b)
Answer:
Option A) Discrete and quantitative
Step-by-step explanation:
We are given the following situation in the question:
In a study of the effect of handedness on athletic ability.
Variable 1: Handedness - right-handed, left-handed, and ambidextrous
Variable 2: Athletic ability measured on a 12-point scale.
Dependent Variable:
- The dependent variable is the response variable and its value depends on the independent variable.
- A change in independent variable leads to a change in the dependent variable.
For the given case the athlete ability is the dependent variable that depends on the independent variable of handedness.
Athletic ability is measured on a 12 point scale. thus, it can take numerical values from 0 to 12.
Thus, it is a quantitative variable.
Since theses values are always expressed in whole numbers and not in decimals so they cannot take all the values within an interval.
Thus, it is a discrete variable.
Option A) Discrete and quantitative
