Answer:1234567890
Step-by-step explanation:101112131415161789995657
Step-by-step explanation:
To check out how efficient or accurate a model is, we use the akaike information criterion or the Bayesian. If the AIC or BIC are lower, then this model would be better. They are also used to control for model complexity
Akaike information criterion = 2k-2ln where k is the number of parameter. A higher k gives a higher AIC.
In the real world complex models are discouraged and avoided since
1. They cause data to be over fitted and can capture noise and information from this data.
2. They are complex and therefore difficult to interpret
3. They consume a lot of time and computing them has several inefficiencies.
Using these two as measure of performance, we can select optimal choice of independent variable.
With forward/backward regression, we are able to put new variables in the model or remove from it. The best is the one with lowest AIC.
Answer:
-1
Step-by-step explanation:
The line goes down 1 grid square for each grid square to the right. Each grid square represents 1 unit in both the x- and y-directions. That means the slope is ...
m = rise/run = -1/1 = -1
The slope of the line is -1.
<span>Graph y=3x^2 -5 and it's inverse.</span>
Answer:
The minimum sample size must be 1118 to have margin of error within one percentage point.
Step-by-step explanation:
We are given the following in the question:
Germination rate = 97% = 0.97
Margin of error = 1% = 0.01
We have to find the minimum sample size for a 95% confidence interval.
Formula for margin of error:
Putting values, we get,
Rounding off to integer,
Thus, the minimum sample size must be 1118 to have margin of error within one percentage point.
