What function best models the data and what wil be the chicken breast after 50 miutes

Students use linear, quadratic, and exponential functions to model data from tables and choose the regression

most appropriate to a given context. They use the correlation coefficient to determine the accuracy of a

regression model and then interpret the function in context. They then make predictions based on their model

and use an appropriate level of precision for reporting results and solutions.  

Lesson 7 focuses on data sets that cannot be modeled accurately, and students are asked

to articulate why. Students use skills learned in Lesson 14 of Module 2 (where they used

calculators to write linear regressions) and apply similar techniques for data sets that are

better suited to modeling with quadratic or exponential regressions. Students use that

same technique to find linear regressions and use their graphing calculators to examine

the correlation coefficient and to find quadratic and exponential regressions. They

compare correlation coefficients to determine which model is best for the data.

Ultimately, students choose the regression model (linear, quadratic, or exponential) most

appropriate to a given data set and then write, verify, and interpret these models in

context. Students need a graphing calculator to complete this lesson. Graphing calculator

instructions are provided, but steps may vary slightly depending on the model of the

graphing calculator.

Refer to the following full modeling cycle during this lesson (Found on page 61 of the CCLS

and page 72 of the CCSSM).

Scaffolding:

 Students are more

engaged when working

with relevant and real data

that interests them.

Websites that provide

data sets are a good

resource for classroom

investigations.

 This lesson might need to

be divided into two days if

students need more time

to master the technology.

Step-by-step explanation:

introduction, methodology, results, discussion

step-by-step explanation:

an observational study is one which consists of actual observation to record data and then analyse the data.

there are a number of factors that should be analyzed before starting an observational study.

the main four factors are:

i) introduction:   this should be analysed to check whether the purpose of the study is correctly established and the data recorded are appropriate for the study

methodology:   the method of collecting the data, such as whether randomly selected, and whether sample size matches with the population to be studied, whether questions asked are easy to answer by common men, etc.

results: then results such as summary of data with comments should be studied thoroughly

discussion:   the last is the discussion, this can be either by management people or persons who are all interested , etc.

(x3 + 6x2 + 2x - 6) • (x - 1)

step-by-step explanation:

polynomial long division :

3.2     polynomial long division

dividing :   x4+5x3-4x2-8x+6

                              ("dividend")

by         :     x-1     ("divisor")

dividend     x4   +   5x3   -   4x2   -   8x   +   6

- divisor   * x3     x4   -   x3            

remainder         6x3   -   4x2   -   8x   +   6

- divisor   * 6x2         6x3   -   6x2        

remainder             2x2   -   8x   +   6

- divisor   * 2x1             2x2   -   2x    

remainder               -   6x   +   6

- divisor   * -6x0               -   6x   +   6

remainder                     0

quotient :   x3+6x2+2x-6   remainder:   0