There are 10 millimeters in 1 centimeter. from that, we can calculate that one centimeter is equivalent to 30 meters. We are trying to find how many meters are in two centimeters so we multiply 30 meters by 2 and get the final answer of 60 meters.
2 Centimeters = 60 Meters
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1) Start with 4 and add 2 repeatedly
2) Start with 2 and multiply by 2 repeatedly
3) 15, 18, 21
If <em>c</em> > 0, then <em>f(x</em> - <em>c)</em> is a shift of <em>f(x)</em> by <em>c</em> units to the right, and <em>f(x</em> + <em>c)</em> is a shift by <em>c</em> units to the left.
If <em>d</em> > 0, then <em>f(x)</em> - <em>d</em> is a shift by <em>d</em> units downward, and <em>f(x)</em> + <em>d</em> is a shift by <em>d</em> units upward.
Let <em>g(x)</em> = <em>x</em>. Then <em>f(x)</em> = <em>g(x</em> + <em>a)</em> - <em>b</em> = (<em>x</em> + <em>a</em>) - <em>b</em>. So to get <em>g(x)</em>, we translate <em>f(x)</em> to the left by <em>a</em> units, and down by <em>b</em> units.
Note that we can also interpret the translation as
• a shift upward of <em>a</em> - <em>b</em> units, since
(<em>x</em> + <em>a</em>) - <em>b</em> = <em>x</em> + (<em>a</em> - <em>b</em>)
• a shift <em>b</em> units to the right and <em>a</em> units upward, since
(<em>x</em> + <em>a</em>) - <em>b</em> = <em>x</em> + (<em>a</em> - <em>b</em>) = <em>x</em> + (- <em>b</em> + <em>a</em>) = (<em>x</em> - <em>b</em>) + <em>a</em>.
Answer:
1 = 39 degrees (some theorem, like triangles sharing a bisector or something sorry)
3 = 51 degrees (if 1=39 and 2=90 degrees since its on a right angle, and a triangle's angles add up to 180, then you subtract 1 and 2 from 180 and get 51
Answer:
No it is not satisfied
Step-by-step explanation:
The one-way ANOVA is used to measure whether the difference between the means of two independent groups are statistically significant.
For it to be satisfied, there has to be one independent variable which is categorical and one dependent variable. The dependent variable on its own has to be a continuous variable
The assumptions are:
1. Equal variance between population
2. Independence between observations
3. The random samples have to be gotten from a normal population.
