Answer:
multiply 200 by .8
its 160
Step-by-step explanation:
Answer, step-by-step explanation:
A. With the previous exercise we can deduce that there is the situation of a number of sales in a grocery store, the relative frequency for the number of units sold, is shown below:
units sold. relative frequency. Acumulative frequency. interval of random numbers
30. 0.16. 0.16. 0.00 <0.16
40. 0.24. 0.4. 0.16 <0.4
50. 0.3. 0.7. 0.4 <0.7
60. 0.2. 0.9. 0.7<09
70. 0.1. 1. 0.9<1
B. For the next point, they give us some random numbers and then it is compared with the simulation of 10 days in sales:
random Units
number. sold
0.12. 30
0.96. 70
0.53. 50
0.80. 60
0.95. 70
0.10. 30
0.40. 50
0.45. 50
0.77. 60
0.29. 40
the two lists are compared so that opposite each one is the result of the simulation
Answer:
D. method of least squares
Step-by-step explanation:
The Least Squares Method (LSM) is a mathematical method used to solve various problems, based on minimizing the sum of the squared deviations of some functions from the desired variables. It can be used to “solve” over-determined systems of equations (when the number of equations exceeds the number of unknowns), to find a solution in the case of ordinary (not redefined) linear or nonlinear systems of equations, to approximate the point values of a function. OLS is one of the basic regression analysis methods for estimating the unknown parameters of regression models from sample data.
Correlation analysis is a statistical method used to assess the strength of the relationship between two quantitative variables. A high correlation means that two or more variables have a strong relationship with each other, while a weak correlation means that the variables are hardly related. In other words, it is a process of studying the strength of this relationship with available statistics.
Analysis of Variance (or ANOVA) is a collection of statistical models used to analyze group averages and related processes (such as intra- and inter-group variation) in statistical science. When using Variance Analysis, the observed variance of a specified variable is divided into the variance component that can be based on different sources of change. In its simplest form, "Analysis of Variance" is a inferential statistical test to test whether the averages of several groups are equal or not, and this test generalizes the t-test test for two-groups to multiple-groups. If multiple two-sample-t-tests are desired for multivariate analysis, it is clear that this results in increased probability of type I error. Therefore, the variance analysis would be more useful to compare the statistical significance of three or more means (for groups or for variables) with the test.
Regression analysis is an analysis method used to measure the relationship between two or more variables. If analysis is performed using a single variable, it is called univariate regression, and if more than one variable is used, it is called multivariate regression analysis. With the regression analysis, the existence of the relationship between the variables, if there is a relationship between the strength of the information can be obtained. The logic here is that the variable to the left of the equation is affected by the variables to the right. The variables on the right are not affected by other variables. Not being influenced here means that when we put these variables into a linear equation in mathematical sense, it has an effect. Multiple linearity, sequential dependency problems are not meant.
D. is the answer
random words to fill the 20 word count
One way ti find the common denominatir is to check ti see if ine denominator is a factor to the other deniminator if it is then the deniminator can be used as the common denominator when the two deniminators are the same compare the numerators
