Answer:
Figure (i) and (iv)
Step-by-step explanation:
Given:
Optional figure is given in attached file.
We need to find two figures that are similar to the 5 by 10 figure.
All the given figure are 
form.
Where m represent the number of rows and n represent the number of columns.
Solution:
Observe that in the given figure 5 by 10, the number of rows is 5 and number of columns is 10, that is, the number of columns is double of that the number of rows.
So we need to find two such figures whose number of columns is double of the number of rows.
From the given figures, figure (i) the number of rows is 2 and number of columns is 4, which is double of number of rows. so it is similar to 5 by 10 figure.
Similarly in figure (iv), the number of rows is 4 and number of columns is 8. so the number of columns is double the number of rows, so it is similar to the figure 5 by 10.
Therefore, the two figures that are similar to 5 by 10 figure are given in attached file such as (i) and (iv).
Answer:y74
Step-by-step explanation:
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:
Research Hypothesis solves the problem by .....
Step-by-step explanation:
Research Hypothesis is a set of assumed statements, consisting certain variables & their relationships
The variables whose relationship are to be checked by hypothesis testing, are independent & dependent variables. The causal variable(s) are independent variables & the effected variable is the dependent variable.
- Null Hypothesis : It is the hypothesis assuming no statistically significant relationship between independent & dependent variables
- Alternate Hypothesis : It is the hypothesis assuming statistically significant relationship between independent & dependent variable
Example : To check the research question, of relationship between research variables, by formulating hypothesis assumed statement
Y = b0 + b1X ; where
Y = dependent variable, X = independent variable, b0 = autonomous, b1 = X intercept on Y
- H0 : b1 = 0 {No significant relationship between X & Y}
- H1 : b1 ≠ 0 {Significant relationship between X & Y}
This way : Research hypothesis solves the problem by - formulating hypothesis assumptions, which recognise the variables & their relations. At last, acceptance of null or alternate hypothesis gives the final research conclusion & interpretation
The answer is b. I just did the question and that is the answer
