Give a brief analysis on the graph given in the picture by using the data (Dominant behaviors of reisdent male with or without injecting octopamine) ABCFGITreatment1: Male vs FemaleTreatment2: Male vs MaleTreatment3: Injected Male vs MaleFocal MaleDomSubDomSubDomSub1A333817666581B347019704621037025402681D113557501E12331427591F104328332581G242454431H70155814462A187143332B3636663201611652D5814532E44218412F452602G52572H35211442 Dominant behaviors of Focal Males towards IntruderMales(T2) vs number of Dominant behaviors of OctopamineInjected Focal Males towards Intruder Males(T3)5045434036353528191818171415 141414103 4440 01 2 36 7 8 9 10111213141516ITreatment 1(Dom)ITreatment 2(Dom)Dominant behaviors25

From the given graph, The dominant behaviors are given for treatment 1 and treatment 2. From the…

Answered: Give a brief analysis on the graph…

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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Forest bathing, also called Shinrin-yoke, is the practice of taking short, leisurely walks in a forest to enhance positive health. To test if forest bathing and mood are related, a clinical psychologist records the time spent forest bathing in minutes (X) and the corresponding change I mood using a standard self report affect grid (Y) among 8 patients with a history of depression. The data are given in the following table. times spent forest bathing (in minutes) change in mood X Y 32 +24 24 +20 28 +25 17 +22 12 +16 Compute the method of least squares to find the equation of the regression line. Use the regression equation computed in part (a) to determine the predicted change in mood of a person who spends 20 minutes forest bathing.
The data below was taken from the fat (g) and sodium (mg) found in different types of food found at fast food restaurants. 19 31 34 35 39 39 43 _y 920 1310 860 1180 940 1260 1500 a) Find the p-value to determine if there is a linear correlation between fat (g) and sodium (mg). Record the p-value below. Round to four decimal places. p-value = b) Is there a linear correlation between fat (g) and sodium (mg)? c) If there is a linear correation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. d) If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places. e) Using the data shown above, predict the the sodium found in fast food when the fat is 32 g. Round your final answer to two decimal places. f) If there is a linear correlation, what percentage of variation in sodium (mg) can be explained by fat (g)? If there is not a linear correlation, leave…
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A study of elementary school children, ages 6 to 11, finds a high positive correlation between shoe size x and score y on a test of reading comprehension. The observed correlation is most likely due to: the effect of a lurking variable, such as age or years of reading experience. a mistake, because the correlation must be negative. cause and effect (larger shoe size causes higher reading comprehension). reverse cause and effect (higher reading comprehension causes larger shoe size).
The following data refers to the amount of caffeine (in mg) consumed by ten university students and their time to complete a practice test (in minutes) for a Economics Exam. Use attached Graph and Table to answer question below pls Describe the overall pattern of the relationship between caffeine amount and time to finish the practice exam in graph diagram provided. Does it follow a straight-line pattern? Is there a positive or negative association, or neither? How strong is the relationship?
After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation
There appears to be a problem with one of your contact methods. Please check your SettingS Enter the following table into your calculator or the Desmos Grapher and create the scatterplot. X 2 60 33 2,100 36 2,860 49 14,440 65 10,560 79 567,860 79 570,560 97 2,238,200 95 3,674,760 98 5282120 1. Is there a correlation for the data? If so, is it strong or weak? 2. What shape of function does the scatterplot show? 3. Use your calculator or the Desmos Grapher to find the equation for the line/curve of best fit. Now, use the equation editor to give the equation for the line/curve of best fit. 4. Determine if this equation is a good predictor of the data, using the appropriate number as proof/reasoning.
. Differentiate between correlation vs. causation. When two variables are correlated (such as strength and running speed), they are associated with one another. Explain how, even if there is a correlation between the two, one might not cause the other. Provide an example of an association between variables where a causal relationship makes sense conceptually. Why can't correlations be used as a tool to prove a causal relationship between variables rather than just an association?

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