Discuss the applications of Statics in real life.

PLEASE PLEASE PLEASE answer both of the questions, and I will give you a thumbs up!

Data contains brain mass in different species versus glia-neuron ratio, the latter being a measurement of brain metabolism as the glia provides the metabolic needs of the neurons.  The relationship between THE LOGARITHM of the brain mass (in the third column) and Glia-neuron ratio (fourth column) appears linear and it is these two variables that we wish to analyze via linear regression.  We would like to know if the human brain fits the trend from the other species.  Towards this end we will perform the regression on all species EXCEPT humans (Homo sapiens).  Again, throw out the human data from your analysis.  You will however need the human numbers for some of the questions.    What is the coefficient of determination (R2) for the data? What is the standard error of the slope of the regression line (SEb) ?

TRUE OR FALSE. If the relationship of x and y is perfectly linear, we can say that x causes y.

When coastal power stations take in large quantities of cooling water, it is inevitable that a number of fish are drawn in with the water. Various methods have been designed to screen out the fish. A particular article examined intake fish catch at an English power plant and several other variables thought to affect fish intake. y = fish intake (number of fish)x1 = water temperature (°C)x2 = number of pumps runningx3 = sea state (values 0, 1, 2, or 3)x4 = speed (knots) Part of the data given in the article were used to obtain the estimated regression equation(based on n = 26). SSRegr = 1486.6 and SSResid = 2230.1 were also calculated. (a) What proportion of observed variation in fish intake can be explained by the model relationship? (Round your answer to four decimal places, if needed.)R2 = (b) Estimate the value of σ. (Round your answer to three decimal places, if needed.)se = (c) Calculate adjusted R2. (Round your answer to four decimal places, if needed.)Adjusted R2 = Adjusted R2…

Heller Manufacturing has two production facilities that manufacture baseball gloves. Production costs at the two facilities differ because of varying labor rates, local property taxes, type of equipment, capacity, and so on. The Dayton plant has weekly costs that can be expressed as a function of the number of gloves produced TCD(X) = X² X + 3 where X is the weekly production volume in thousands of units and TCD(X) is the cost in thousands of dollars. The Hamilton plant's weekly production costs are given by TCH(Y) y² + 2Y + 9 where Y is the weekly production volume in thousands of units and TCH(Y) is the cost in thousands of dollars. Heller Manufacturing would like to produce 5,000 gloves per week at the lowest possible cost. (a) Formulate a mathematical model that can be used to determine the optimal number of gloves to produce each week at each facility. min s.t. = X, Y Z 0 = 5 (b) Use Excel Solver or LINGO to find the solution to your mathematical model to determine the optimal…

Suppose that the number of tee shirts sold (N) depends linearly on the price charged (x). Write an equation showing this dependence.

The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. Round your answers to 3 decimal places y= Raspberry Type Farm A - North Field Farm B - North Field Farm A - South Field Farm B - South Field Farm C -Small Field Farm D Farm E x+ grams 60 65 70 75 80 85 90 Vitamin C content in mg 14.3 16.1 18.9 20.3 22.8 25.5 27.5 According to this model, how many mg of Vitamin C can be expected in a raspberry that weighs 82 grams Round to 3 decimal places.