Step-by-step explanation:
(f+g)(x) = f(x) + g(x)
= x/2-3 + 4x²+x+4
= ..........
Answer:
13/20
Step-by-step explanation:
65%=65/100
65/100=13/20
An inequality which compares the changes in elevation of this hot air balloon while in flight is given by L - 83 2/5 ≤ L ≤ L + 83.7.
<h3>What is an elevation?</h3>
An elevation is also referred to as an altitude and it can be defined as the vertical distance (height) above a natural satellite or the surface of planet Earth such as land or sea level.
This ultimately implies that, an elevation (altitude) simply refers to the vertical height (elevation) of an object or physical body above a particular location or planetary reference plane such as land or sea level on planet Earth.
<h3>What is an inequality?</h3>
An inequality can be defined as a mathematical relation that compares two (2) or more integers and variables in an equation based on any of the following arguments (symbols):
- Less than (<).
- Greater than (>).
- Less than or equal to (≤).
- Greater than or equal to (≥).
For this exercise, let the variable L represent the initial height of this balloon. Also, since the hot air balloon decreased its elevation by 83 2/5 and increases its elevation by 83.7 meters, we have the following:
- The lower limit is equal to: L - 83 2/5.
- The upper limit is equal to: L + 83.7.
In this context, an inequality which models the changes in elevation of this hot air balloon is L - 83 2/5 ≤ L ≤ L + 83.7.
Read more on inequality here: brainly.com/question/6666926
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Answer:
Null hypothesis:
Alternative hypothesis:
Since the p value is very low compared to the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true percent of people with type A of blood is significantly different from 0.4 or 40%
Step-by-step explanation:
Information given
n=144 represent the random sample taken
X=81 represent the number of people with type A blood
estimated proportion of people with type A blood
is the value that we want to verify
represent the significance level
z would represent the statistic
![p_v{/tex} represent the p value Hypothesis to testWe want to test if the percentage of the population having type A blood is different from 40%.: Null hypothesis:[tex]p=0.4](https://tex.z-dn.net/?f=p_v%7B%2Ftex%7D%20represent%20the%20p%20value%20%3C%2Fp%3E%3Cp%3E%3Cstrong%3EHypothesis%20to%20test%3C%2Fstrong%3E%3C%2Fp%3E%3Cp%3EWe%20want%20to%20test%20if%20the%20percentage%20of%20the%20population%20having%20type%20A%20blood%20is%20different%20from%2040%25.%3A%20%20%3C%2Fp%3E%3Cp%3ENull%20hypothesis%3A%5Btex%5Dp%3D0.4)
Alternative hypothesis:
the statistic is given by:
(1)
Replacing the info given we got:
Now we can calculate the p value with this probability taking in count the alternative hypothesis:
Since the p value is very low compared to the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true percent of people with type A of blood is significantly different from 0.4 or 40%
