**Title: Correlation Analysis between Lyme Disease and Drowning Deaths****Overview:**Lyme disease is an inflammatory condition characterized by a skin rash and flu-like symptoms, transmitted through the bite of an infected deer tick. This activity investigates the data representing reported cases of Lyme disease and drowning deaths in a rural county. The tasks involve selecting a scatter plot, computing the linear correlation coefficient, and analyzing the possible existence of a relationship between the two variables.**Instructions:**1. **Scatter Diagram:** - Four scatter plots (A, B, C, D) are provided. The plots compare Lyme disease cases (x-axis) with drowning deaths (y-axis). - Task: Choose the correct graph that best fits the data.2. **Linear Correlation Coefficient:** - Calculate the linear correlation coefficient (r) for Lyme disease cases and drowning deaths. - Task: Determine and round the value of \( r \) to three decimal places.3. **Existence of Linear Relation:** - Evaluate if a linear relationship exists based on the value of \( r \). - Determine if the correlation coefficient is statistically significant by comparing it to a given critical value. - Task: Decide if the relationship is significant and which variables are associated.4. **Analysis Question:** - Consider if an increase in Lyme disease causes an increase in drowning deaths and identify any lurking variables. - Options: - (A) No cause and effect, no lurking variables. - (B) Potential cause and effect, no lurking variables. - (C) No cause and effect, temperature and time of year as lurking variables. - (D) No cause and effect, pesticide control and life guards as lurking variables. - Task: Select the most plausible explanation.**Diagram Details:**- All graphs have axes labeled as "Lyme Disease" on the x-axis and "Drownings" on the y-axis with scaling from 0 to 30.- The data points suggest different patterns of correlation, aiding in identifying the correct plot and assessing the relationship strength.By completing this exercise, you'll learn about the correlation between variables and the potential influence of external factors or lurking variables on observed data trends. **Title: Analysis of Lyme Disease and Drowning Deaths Data**---**Lyme Disease Overview:**Lyme disease is an inflammatory disease that causes a skin rash and flu-like symptoms. It is transmitted through the bite of an infected deer tick. The following data analysis aims to explore the relationship between reported Lyme disease cases and drowning deaths in a rural county.**Data and Tasks:**Complete the tasks a) through c) using the provided data:1. **Draw a Scatter Diagram:** - Plot the number of drowning deaths on the y-axis against Lyme disease cases on the x-axis. - Example chart shows some clustering at lower numbers of Lyme disease cases and drowning deaths.2. **Determine the Linear Correlation Coefficient:** - Calculate the correlation to assess the relationship between Lyme disease cases and drowning deaths. - Round your answer to three decimal places.3. **Analyze Linear Relationship:** - Using the calculated correlation coefficient, determine if a linear relationship exists. - Consider possible correlations such as increase in Lyme disease cases potentially affecting drowning deaths.**Data Tables:**- **Cases and Deaths Data:** - **Columns:** Cases of Lyme Disease, Drowning Deaths, Month - **Data:** - (2, 0, J), (2, 1, F), (2, 2, M), (5, 9, A), - (15, 9, M), (22, 17, J), (13, 5, J), (9, 5, A), - (8, 2, S), (4, 3, O), (5, 0, N), (1, 0, D)- **Critical Values for Correlation Coefficient:** - **Column:** n (sample size) - **Data:** Values decrease from 0.997 for n=3 to 0.396 for n=30.**Conclusion:**Review the calculated statistics to understand the relationship between Lyme disease incidences and drowning deaths. Use this analysis to explore potential patterns or causes based on variations in data by month and other identified factors.---This transcription provides students and educators with data for analysis, exploring epidemiology and statistics while considering real-world impacts of disease data.

a) Step-by-step procedure to draw scatter diagram using Excel: In Excel sheet, enter Cases of Lyme…

Lyme disease is an inflammatory disease that results in a skin rash and flulike symptoms. It is transmitted through the bite of an infected deer tick. The following data represent the drowning deaths for a rural county. Complete parts (a) through (c) below. A Click the icon to view the table of Lyme disease and drowning deaths. E Click the icon to view the critical values table. ..... (a) Draw a scatter diagram of the data. Choose the correct graph below. Oc. OD. OA. O B. ADrownings A Drownings 20 ADrownings 204 ALyme Disease 20- 20- 30 30 30 Lyme Disease Lyme Disease Lyme Disease Drownings (b) Determine the linear correlation coefficient between Lyme disease and drowning deaths. The linear correlation coefficient between Lyme disease and drowning deaths isr= (Round to three decimal places as needed.) (c) Does a linear relation exist between the number of reported cases of Lyme disease and the number of drowning deaths? The variables Lyme disease and drowning deaths are V associated because r is and the absolute value of the correlation coefficient, , is V than the critical value, (Round to three decimal places as needed.) Question View Do you believe that an increase of Lyme disease causes an increase in drowning deaths? What is a likely lurking variable between cases of Lyme disease and drowning deaths? O A. An increase in Lyme disease does not cause an increase in drowning deaths. There are no lurking variables. B. An increase in Lyme disease causes an increase in drowning deaths. There are no lurking variables. O C. An increase in Lyme disease does not cause an incrbase in drowning deaths. The temperature and time of year are likely lurking variables. O D. An increase in Lyme disease does not cause an increase in drowning deaths. Pesticide control and life guards are likely lurking variables.

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P