Complete the recursive formula of the geometric sequence 16\,,\,3.2\,,\,0.64\,,\,0.128,...16,3.2,0.64,0.128,
Nastasia [14]
Answer:
for all n>0,
Step-by-step explanation:
Let
be the sequence described.
A geometric sequence has the following property: there exists some r (the ratio of the sequence) such that
forr all n>0.
To find r, note that

Similarly


Thus
for all n>0, and
Answer:
1st angle: 128°
2nd angle: 32°
3rd angle: 20°
Step-by-step explanation:
You can start by setting up an equation. 180=x+4x+x-12. It sould all add up to 180 because angles of a triangle always add up to 180, and x represents the second triangle (you use the second angle as x because the other two angles elaborate off of this second angle). Then you solve. Add 12 to 180 and get 192. Then you can add like terms and make it 192=6x (you add the x's together). Lastly divide 192 by 6 and get 32. So the measurement of angle 2 is 32°. Then you multiply 32 by 4 to get the 1st angle measure, being 128. Lastly subtract 12 from 32 and get 20 for angle three. To check you work add the three angle measures you got and see if they =180, if so then you are correct.
The term for a point that varies greatly from all other data points is known as an <u>OUTLIER</u>
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Explanation:
- An outlier is a data point that differs significantly from other observations. An outlier may be due to variability in the measurement or it may indicate experimental error.
- An outlier can cause serious problems in statistical analyses.
- An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. In a sense, this definition leaves it up to the analyst to decide what will be considered abnormal.
- A point that falls outside the data set's inner fences is classified as a minor outlier, while one that falls outside the outer fences is classified as a major outlier.
- The data here appear to come from a linear model with a given slope and variation except for the outlier which appears to have been generated from some other model.
- Outliers can occur by chance in any distribution, but they often indicate either measurement error or that the population has a heavy-tailed distribution.
1.<u>3 </u>x 1= 1.<u>3 </u>hope this helped
The last two options are correct, but it looks like you’ve got them :)