Sin x3D%=

Find the linear curve fit coefficients. Use equations (4a) and (4b) to find these coefficients and determine the units of the coefficients, c1 and c2. Note that the units for these coefficients will not be the same in our two cases. Further note that the calibration coefficients are intermediate quantities, not final results. It is probably best to keep them to four significant digits to avoid round-off errors in subsequent calculations. Lastly, plot the line representing the curve fit. It should appear as a best fit, if you’ve done everything correctly. n is the number of data pairs in the curve-fit. the yi ’s arethe ordinate values (the less precisely known). the xi ’s are the abscissa values (the more precisely known).

A chemistry experiment is performed measuring the solubility of potassium chloride (KCl) in water at different temperatures. The goal was to determine if there is a linear relationship between the temperature of the water and how much KCl can dissolve, measured as grams per 100 milliliter (g/100mL). After the experiments were performed, the following data was collected with temperature being the independent x-variable and solubility being the dependent y-variable: Temperature (°C) x Solubility (g/100mL) y 10 31 20 33 30 37 40 41 50 42 Based on the data given for temperature and solubility of KCl and without doing any math yet, which of the following do you predict would best describe the relationship between these variables?     A positive linear relationship (r close to 1)     A positive linear relationship (r close to -1)     A negative linear relationship (r close to 1)     A negative linear relationship (r close to -1)…

The number of banks in a country has been dropping steadily since 1984, and the trend in recent years has been roughly linear. The annual data for the years 1999 through 2008 can be summarized as follows, where x represents the years since 1990 and y the number of banks, in thousands. n=10 Ex-235 ²-5605 Ey-77.564 Ey²=603.80424 Exy-1810.155 a. Find an equation for the least squares line. b. Use your result from part a to predict the number of banks in the year 2020. c. If this trend continues linearly, in what year will the number of banks drop below 6200? d. Find and interpret the correlation coefficient.