The El Nino phenomenon has significant impacts on the global distribution of weather and onthe flow of most tropical rivers. Consider the data in Table below on the anomaly of sea surfacetemperature in the Pacific Ocean in degree Centigrade (an index of El Nino) and the annual flowof the Nile river in cubic kilometers for the period 1972 -1985.Year 1972 19731974 1975 1976 1977 1978 1979 1980 1981-1.1-0.8-1.3-1.30.21.7-0.5-0.70.3-0.51138312111196701341249792Where, t temperature (°C) and f= flow (km/year)Estimate the linear regression between the two variables (1 and f).

Given that, The El Nino phenomenon has significant impacts on the global distribution of weather and…

Answered: The El Nino phenomenon has significant…

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 numbers of polio cases in the world are shown in the table for various years. Year Number of Polio Cases (thousands) 1988 1992 1996 2000 2005 2007 350 138 32 6 3.2 1.3 Let f(t) be the number of polio cases (in thousands) t years after 1980. Copy the data to Desmos to draw a scatterplot of the data. Make sure to adjust the years so they represent years after 1980. a) Is it better to model the data with a linear or with an exponential model? Select an answer b) Use regression in Desmos to find an appropriate model for f. Make sure to check Log mode in the parameter window in Desmos if you are fitting an exponential model. f(t) places. Round the coefficients to 4 decimal Hint: Use the variable t from the drop down menu when entering the equation. Do not just type in t. c) Predict the number of polio cases in 2019. d) Find the approximate half-life of the number of polio cases. Round the answer to one decimal place. years
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A researcher studies water clarity at the same location in a lake on the same dates during the course of a year and repeats the measurements on the same dates 5 years later. The researcher immerses a weighted disk painted black and white and measures the depth (in inches) at which it is no longer visible. The collected data is given in the table below. Complete parts (a) through (c) below Observation 1 2 3 4 5 6 1/25 3/19 5/30 7/3 9/13 11/7 41.6 72.7 72.4 65.9 64.2 68.6 49.3 72.1 76.6 69.4 69.8 70.5 Date Initial Depth, X, Depth Five Years Later, Y, a) Why is it important to take the measurements on the same date? CA. Using the same dates makes it easier to remember to take samples. B. Using the same dates maximizes the difference in water clarity. OC. Those are the same dates that all biologists use to take water clarity samples. D. Using the same dates makes the second sample dependent on the first and reduces variability in water clarity attributable to date. b) Does the evidence…
When water flows across farmland, some soil is washed away, resulting in erosion. An experiment was conducted to investigate the effect of the rate of water flow (liters per second) on the amount of soil (kilograms) washed away. The data are given in the following table: Flow rate 0.31 0.85 1.26 2.47 3.75 Eroded soil 0.82 1.95 2.18 3.01 6.07 Let xx represent the flow rate variable and yy represent the variable for soil eroded. Then \bar x = 1.73, s_x = 1.38, \bar y = 2.81, s_y = 1.99xˉ=1.73,sx=1.38,yˉ=2.81,sy=1.99 Use this to complete the following calculation of the correlation coefficient for these data. r = \frac{1}{n-1}\left[\left(\frac{x_1 - \bar x}{s_x}\right)\left(\frac{y_1 - \bar y}{s_y}\right) + \left(\frac{x_2 - \bar x}{s_x}\right)\left(\frac{y_2 - \bar y}{s_y}\right) + \cdots + \left(\frac{x_n - \bar x}{s_x}\right)\left(\frac{y_n - \bar y}{s_y}\right)\right]r=n−11[(sxx1−xˉ)(syy1−yˉ)+(sxx2−xˉ)(syy2−yˉ)+⋯+(sxxn−xˉ)(syyn−yˉ)]…
An article in Air and Waste ("Update on Ozone Trends in California's South Coast Air Basin," Vol. 43, 1993) studied the ozone levels on the South Coast air basin of California for the years 1976-1991. The author believes that the number of days that the ozone exceeds 0.20 parts per million depends on the seasonal meteorological index (the seasonal average 850 millibar temperature). The data follow: Year Days Index 16.3 1976 91 1977 105 17.1 1978 106 18.2 1979 108 18.1 1980 88 17.2 1981 91 18.2 1982 58 16.0 1983 82 17.2 Round your answers to 2 decimal places. (a) Fit a simple linear regression model to the data. Test for significance of regression using a = 0.05. y = i Calculate fo: i Year Days Index 1984 82 17.7 1985 65 17.2 1986 61 16.9 1987 48 17.1 1988 61 18.2 1989 43 17.3 1990 33 17.5 1991 36 16.6 i + i Is the simple linear regression model significant? No. (b) Calculate a 95% confidence interval on the slope. ≤B₁ ≤i X
Perform a chi-square independence test, provided the conditions for using the test are met. Researchers studied the bone mineral density (BMD) and depression of men aged 65 to 92 years. At the 1% significance level, do the data in the table (taken from a random sample) provide sufficient evidence to conclude that BMD and depression are statistically dependent for elderly men? Click on the icon to view the data table. What are the null and alternative hypotheses? O A. Ho: BMD is dependent upon depression in elderly men. H₂: Depression is dependent upon BMD in elderly men. B. Ho: Depression and BMD in elderly men are statistically dependent. H₂: Depression and BMD in elderly men are statistically independent. O C. Ho: Depression and BMD in elderly men are statistically independent. H₂: Depression and BMD in elderly men are statistically dependent. Find the test statistic. x² = Find the P-value. P= (Round to four decimal places as needed.) What is the conclusion of the independence test?…
What happens visually when SSE goes to zero and SSE goes to SST in statistics
Systolic coefficients of variation are 14.2% and the Diastolic is 17% The coefficients of variation for each data set are: a. more than 5 percentage points apart b. within 5 percentage points of each other Therefore, the systolic measurements vary a. about the same as b. significantly more than c. significantly less than the diastolic measurements.
How sensitive to changes in water temperature are coral reefs? To find out, scientists examined data on sea surface temperatures and coral growth per year at locations in the Gulf of Mexico and the Caribbean Sea. The table shows the data for the Gulf of Mexico. Sea surface temperature 26.726.7 26.626.6 26.626.6 26.526.5 26.326.3 26.126.1 Growth 0.850.85 0.850.85 0.790.79 0.860.86 0.890.89 0.920.92 Click to download the data in your preferred format. CSV Excel JMP Mac-Text Minitab14-18 Minitab18+ PC-Text R SPSS TI CrunchIt! © Macmillan Learning (a) Make a scatterplot. Which is the explanatory variable? The plot shows a negative linear pattern. Explanatory Variable: How sensitive to changes in water temperature are coral reefs? To find out, scientists examined data on sea surface temperatures and coral growth per year at locations in the Gulf of Mexico and the Caribbean Sea. The table shows the data…
A group of researchers studied the effect of acid rain on wildlife and collected n = 12 samples from streams in different States. They recorded the pH (X) of the water (i.e. units above pH 7), and the BCI, a measure of biological diversity (Y). The data obtained is summarized below. DATA: Observation 1 2 3 4 5 6 7 8 9 10 11 12 pH above 7 (X) 0.65 0.50 0.93 0.86 1.02 0.94 1.16 1.24 1.30 1.45 1.85 1.89 Units of BCI (Y) 14.5 22.9 15.8 38.3 18.9 20.0 21.4 23.8 23.6 25.2 27.3 29.4 Find the correlation coefficient between pH and BCI (round to the nearest hundredth; place your answer in the box below)
Shortleaf Pines. The ability to estimate the volume of a tree based on a simple measurement, such as the diameter of the tree, is important to the lumber industry, ecologists, and conservationists. Data on volume, in cubic feet, and diameter at breast height, in inches, for 70 shortleaf pines was reported in C. Bruce and F. X. Schumacher’s Forest Mensuration (New York: McGraw-Hill, 1935) and analyzed by A. C. Akinson in the article “Transforming Both Sides of a Tree” (The American Statistician, Vol. 48, pp. 307–312). The data are provided on the WeissStats site. a. obtain and interpret the standard error of the estimate. b. obtain a residual plot and a normal probability plot of the residuals. c. decide whether you can reasonably consider Assumptions 1–3 for regression inferences met by the two variables under consideration.
The numbers of polio cases in the world are shown in the table for various years. Year Number of Polio Cases (thousands) 1988 1992 1996 2000 2005 2007 350 138 33 3 3.2 1.3 Let f(t) be the number of polio cases (in thousands) t years after 1980. Copy the data to Desmos to draw a scatterplot of the data. Make sure to adjust the years so they represent years after 1980. a) Is it better to model the data with a linear or with an exponential model? [Select an answer b) Use regression in Desmos to find an appropriate model for f. Make sure to check Log mode in the parameter window in Desmos if you are fitting an exponential model. f(t) Round the coefficients to 4 decimal places. Hint: Use the variablet from the drop down menu when entering the equation. Do not just type in t. c) Predict the number of polio cases in 2013. d) Find the approximate half-life of the number of polio cases. Round the answer to one decimal place. years

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