It depends really. If you stay close to the present, then predicting future results isn't too bad. The further you go out, the more unpredictable things get. This is because the points may deviate from the line of best fit (aka regression line) as time wears on. Of course, it also depends on what kind of data we're working with. Some pairs of variables are naturally going to correlate very strongly together. An example would be temperature versus ice cream sales.
A sample size of 60 is required.
We use the formula

We first find the z-score associated with this level of confidence:
Convert 99% to a decimal: 99/100 = 0.99
Subtract from 1: 1-0.99 = 0.01
Divide by 2: 0.01/2 = 0.005
Subtract from 1: 1-0.005 = 0.995
Using a z-table (http://www.z-table.com) we see that this value is equally distant from 2.57 and 2.58; therefore we will use 2.575:
Total weight = 50 lb
x = number of 3-lb weights
y = number of 10-lb weights
weight of 3-lb weights = 3x
weight of 10-lb weights = 10y
total weight = 3x + 10y
equation
3x + 10y = 50
The answer is: "11 %" .
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There is 11% of fruit in the cake.
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Explanation:
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275g is what percent of 2.5 kg?
First, convert "275 g" into "kg".
Note the exact conversion: 1000 g = 1 kg .
So 275 g = (275/1000) kg = 0.275 kg .
0.275 kg = (n/100) * 2.5 kg ;
→ (n/100) * 2.5 = 0.275 ;
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Divide each side by "(2.5)"
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→ (n/100) = (0.275) / (2.5) ;
→ (n/100) = 0.11 ;
Multiply each side by "100" ;
n = 11 .
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The answer is: 11 % .
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Answer:
this is the answer 25
Step-by-step explanation:
i guessed