In what way is the second plot more (or less) useful in describing the relationship between the variables? plt.scatter (my_data['SNWD'], my_data['Deliveries'])plt.xlabel('Snow Depth (SNWD)')plt.ylabel('Deliveries')plt.title('Scatterplot of Depth of Snow on Ground vs. Deliveries')plt.show()7070Scatterplot of Depth of Snow on Ground vs. Deliveries6050Deliveries.4030202010100.02.55.07.510.012.515.017.5Snow Depth (SNWD) sns.regplot(x='SNWD', y='Deliveries', data=my_data)plt.title('Regplot of Depth of Snow On Ground vs. Deliveries')plt.xlabel('Snow Depth')plt.ylabel('Deliveries')plt.show()Regplot of Depth of Snow On Ground vs. Deliveries707060-5050•..4040Deliveries30B1020-Oe10100.02.55.07.510.012.515.017.5Snow Depth

The regression line in the second plot helps to quantify the relationship between the variables by…

Answered: plt.scatter (my_data['SNWD'],…

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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The data (Table 1) show the lists of sugar consumption (kg per capita) and the number of diabetes patients (per million people) for selected countries. Table 1: Sugar consumption and diabetes patients Sugar diabetes patients 5 6 4 4 5 a) b) 6 9 3 2 11 Construct a scatter plot, and comment on the features of the plot. Does there appear to be a linear relationship between the two variables? How would you characterize the relationship? c) Compute the value of the correlation coefficient. Is the value of r consistent with your answer to part (b)? d) Is it reasonable to conclude that by sugar consumption against the number of diabetes patients? Explain.
2. Which model-linear, quadratic, or exponential-seems most appropriate for this scatter plot? X
A study by Judge and Cable (2010) suggests that there is a positive relationship between weight and income for a group of men. The following data is similar to what was collected in the study. To simplify the weight variable, the men are categorized into five categories that measure actual weight relative to height from 1=thinnest to 5=heaviest. Income is recorded as thousands earned annually. Weight (X) Income (Y) 4 151 5 88 3 52 2 73 1 49 3 92 1 56 5 143 a. Calculate the Pearson correlation for these data. b. Is the correlation statistically significant? Use a two-tailed test with a=.05.
A researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content. His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is ŷ= -299.48 + 4.35 x Calories 186 181 176 149 184 190 158 139 175 148 Sodium 495 477 425 322 482 587 370 322 479 375 Interpret the slope in terms of this problem. If appropriate, find the sodium content if the calorie content is 170. If not, why? If appropriate, find the sodium content if the calorie content is 136. If not, why?
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How much should a healthy Shetland pony weigh? Let x be the age of the pony (in months), and let y be the average weight of the pony (in kilograms). x 3 6 12 15 21 y 60 95 140 172 173 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. A scatter diagram has a horizontal axis labeled "x (age (in months))" with values from 60 to 173 and a vertical axis labeled "y (average weight (in kg))" with values from 3 to 21. The scatter diagram has 5 points. A pattern goes up and right from (60, 3) to (173, 21). A scatter diagram has a horizontal axis labeled "x (age (in months))" with values from 3 to 21 and a vertical axis labeled "y (average weight (in kg))" with values from 60 to 173. The scatter diagram has 5 points. A pattern goes down and right from (3, 173) to (21, 60). A scatter diagram has a horizontal axis labeled "x (age (in months))" with values from 3 to 21 and a vertical axis labeled "y (average weight (in kg))" with…
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 arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.

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