Ex.5Please specify which answer is to which question please Errors in medical prescriptions occur relatively frequently. In a study, two groups of doctors hadsimilar error rates and one group switched to e-prescriptions while the other continued with hand-written prescriptions. One year later, the number of errors was measured. The results are given inthe two-way table.Error2541478No Error35942370TotalElectronicWrittenTotal(1) Fill in the row and column totals.(2) What proportion of all the prescriptions had errors in them?(3) What proportion of electronic prescriptions had errors in them?(4) What proportion of written prescriptions had errors in them?(5) What proportion of the prescriptions with errors were written prescriptions?

Given data is Error No Error Total Electronic 254 3594 Written 1478 2370 Total…

Answered: Errors in medical prescriptions occur…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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During a particularly dry growing season in a southern state, farmers noticed that there is a delicate balance between the number of seeds that are planted per square foot and the yield of the crop in pounds per square foot. The yields were the smallest when the number of seeds per square foot was either very small or very large. The data in the table show various numbers of seeds planted per square foot and yields (in pounds per square foot) for a sample of fields. A 2-column table with 15 rows. Column 1 is labeled number of seeds (per square foot) with entries 28, 75, 30, 43, 71, 35, 40, 59, 66, 79, 85, 81, 16, 33, 16. Column 2 is labeled yield (pounds per square foot) with entries 131, 171, 132, 166, 169, 150, 161, 183, 173, 161, 147, 157, 86, 145, 86. Which scatterplot represents the seed and yield data? A graph titled number of Seeds and Crop Yield has seeds (per square foot) on the x-axis, and yard (pounds per square foot) on the y-axis. The points curve up to a point, and…
3. When car crash tests were conducted, data were collected that consist of crash test loads (pounds) on the left femur and right femur. When those loads are partitioned into the three car size categories of small, midsize, and large, the two-way analysis of results from XLSTAT are as shown below. (The row factor of femur has the two values of left femur and right femur, and the column factor of size has the three values of small, midsize, and large.) Use a 0.05 significance level to apply the methods of two-way analysis of variance (2 way ANOVA test) in R-studio. Present the related hypotheses of interest. What do you conclude?
Measuring the height of a California redwood tree is very difficult because these trees grow to heights of over 300 feet. People familiar with these trees understand that the height of a California redwood tree is related to other characteristics of the tree, including the diameter of the tree at the breast height of a person. The data in the table represent the height (in feet) and diameter (in inches) at the breast height of a person for a sample of 21 California redwood trees. Assuming a linear relationship, use the least- squares method to compute the regression coefficients b0 and b1. State the regression equation that predicts the height of a tree based on the tree’s diameter at breast height of a person. Interpret the meaning of the slope in this equation. Predict the mean height for a tree that has a breast height diameter of 25 inches. Height Diameter at breast height Bark thickness 122.0 20 1.1 193.5 36 2.8 166.5 18 2.0 82.0 10 1.2 133.5 21 2.0 156.0 29 1.4…
Fast reactions: In a study of reaction times, the time to respond to a visual stimulus x and the time to respond to an auditory stimulus y were recorded for each of 8 subjects. Times were measured in thousandths of a second. The results are presented in the following table. The results are presented in the following table. Use the TI-84 calculator. Visual Auditory 161 159 176 163 178 201 188 193 191 169 211 189 235 241 228 209 Compute the least-squares regression line for predicting the time to respond to an auditory (y) from the time to respond to a visual stimulus (x). Round the slope and y-intercept values to at least four decimal places.
When wildebeest are more abundant, they graze the grass more heavily, so there are fewer fires and moretrees grow. Lions feed more successfully when there are more trees, so the lion population increases. Thedata on one part of this cycle, wildebeest abundance (in thousands of animals) and the percent of the grassarea that burned in the same year are on the spreadsheet. To what extent do these data support the claim that more wildebeest reduce the percent of grasslands that burn? How rapidly does burned area decrease as the number of wildebeest increases? To answer these questions, create a scatterplot and add the regression line. Describe the scatterplot. Interpret the slope and intercept in context of the problem. Does the intercept explanation make sense in the real world? Find the correlation coefficient and coefficient of determination. What do they tell us about the relationship between number of wildebeest and percent of grassland burned? Beest (in 1000s) Percent Burned…
Fast reactions: In a study of reaction times, the time to respond to a visual stimulus x and the time to respond to an auditory stimulus y were recorded for each of 7 subjects. Times were measured in thousandths of a second. The results are presented in the following table. The results are presented in the following table. Visual Auditory 176 163 201 197 188 193 228 209 211 189 203 206 191 169 Compute the least-squares regression line for predicting the time to respond to an auditory (y) from the time to respond to a visual stimulus (x). Round the slope and y-intercept values to at least four decimal places.
Mathematically discuss the role that SST.SSR and SSE play in the determination of the coefficient of determination within a linear least-squares analysis
Row vs. Column Are the data entered in row format or column format? What is one advantage of entering data in row format? For the variables below, state whether they are independent, quasi-independent, or dependent variables in this situation. Briefly explain why. Gender Number Grade
A Find the equation of the least squares line for the data. Round constants to the nearest thousandth B. Use the equation from part A to predict the retail price of a 2010 Corvette with an odometer reading of 30.000.
A random sample of 65 high school seniors was selected from all high school seniors at a certain high school. A scatterplot (not shown) revealed the height, in cm and foot length in cm, for each high school student from the sample. The association was described to be strong, positive, and linear. a. In the context of the study, explain what is meant by the following terms: positive: linear: b. The least squares regression equation was predicted height=105.08+2.599 (foot length). One of the students had a foot length of 20 cm. His residual was calculated to be 2.94 cm. What was the height of the student? c. suppose that the distribution of residuals is approximately normal with a standard deviation of 5.9 cm. What percent of residuals are less than 7 cm? Justify why.
Sales of a particular product for the years 2017 through 2020 have been 47,505, 53,010, 49,385 and 81,933 respectively. What sales would you forecast for 2021 using the simple regression (least squares) method?
A student studying statistics examined whether a relationship exists between the city miles per gallon (mpg) and highway miles per gallon (mpg) for cars and trucks. The miles per gallon of a vehicle describe the typical number of miles the vehicle can drive on one gallon of gas. Using a random sampleof 50 cars and trucks, the student obtained the least squares regression equation: predicted highway mpg = 1.14 .(city mpg) + 5.8 a. Predict the highway mpg for a vehicle that gets an average of 24 miles per gallon when driving in the city. b. Describe the meaning of the number 1.14 in the regression equation above?

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