Statistical analysis of chirps and temperature

In summary, the conversation discusses the application of correlation and regression in analyzing the association between the temperature and the number of times a cricket chirps in a minute. The conversation includes questions on determining the strength of the association, finding the best-fit line, predicting temperature based on chirp rate, and using the results to show causality. The suggested methods include plotting the data, using 2 variable statistics and linear or least squares regression, and finding the correlation coefficient r.
  • #1
xiaobai5883
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Homework Statement



One class application of correlation and regression involves the association between the temperature and the number of times cricket chirps in a minute. Listed below are numbers of chirps in 1 minute and the corresponding temperature in degrees Fahrenheit.

Chirps in 1 min 882 1188 1104 864 1200 1032 960 900
temperature 69.7 93.3 84.3 76.3 88.6 82.6 71.6 79.6

i. Is there sufficient evidence to conclude that there is an association between the number of chirps in a minute and the temperature?
ii. Find the equation of the straight line that best fits the sample data.
iii. If a cricket chirps 1234 times in 1 minute, what is the best predicted value for the temperature?
iv. What percentage of the variation in temperature can be explained by the variation in the cricket chirp rate?
v. Can the correlation/regression results be used to show that changes in temperature cause changes in the cricket chirp rate?

ANYONE PLEASE HELP~

Homework Equations





The Attempt at a Solution

 
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  • #2


the idea is for you to attempt the question first - to get you started try plotting your results for i) then google "2 variable statistics" and "linear regression" or "least squares regression"
 
Last edited:
  • #3


lanedance said:
the idea is for you to attempt the question first - to get you started try plotting your results for i) then google 2 variable statistics and linear or least squares regression

i have already plot those results...
but how to google??
is there any functions or equation or formula that i can use??
 
  • #4


so do you see any correlation in your plot?

the topics in the last post should give you the equations
for i) look at correlation coefficient r in 2 variable statistics
 
  • #5


lanedance said:
so do you see any correlation in your plot?

the topics in the last post should give you the equations
for i) look at correlation coefficient r in 2 variable statistics

you mean that r should be put like...
(Temperature)=r(Chirps in 1 min)??
i think should be
(Temperature)=r(Chirps in 1 min)+c
but in almost every case the r and c is different...
so how how??
 
  • #6


you want to find the line that best fits the data
if
y = chirps
x = temp

then find m and c such that
y = mx + c
to minimise the sum of squared errror between you data points and the line, this is a mathematical way of "eyeballing" the best line through the data

Any scientific calculator or spreadsheet package should be able to give you m and c

the correlation coefficient r, ranging form 0 to 1 is a measure of how well correlated your data, ie how close to a line
 
  • #7


lanedance said:
you want to find the line that best fits the data
if
y = chirps
x = temp

then find m and c such that
y = mx + c
to minimise the sum of squared errror between you data points and the line, this is a mathematical way of "eyeballing" the best line through the data

Any scientific calculator or spreadsheet package should be able to give you m and c

the correlation coefficient r, ranging form 0 to 1 is a measure of how well correlated your data, ie how close to a line

LOL??
actually can you give me one example??
because i don't know what do you mean actually...
and the correlation coefficient r is what formula??
is there any formula??
 

1. What is the purpose of analyzing chirps and temperature statistically?

The purpose of statistical analysis of chirps and temperature is to understand the relationship between these two variables and to identify any patterns or trends that may exist. This can provide valuable insights into the behavior of certain species of animals and their response to changes in temperature.

2. What statistical methods are commonly used for analyzing chirps and temperature?

Some common statistical methods used for analyzing chirps and temperature include correlation analysis, regression analysis, and ANOVA (analysis of variance). These methods allow for the determination of the strength and direction of the relationship between chirps and temperature, as well as any potential differences in chirp patterns across different temperature levels.

3. How do chirps and temperature relate to each other?

Chirps and temperature are closely related, as chirping is a common behavior exhibited by many animals in response to changes in temperature. As the temperature increases, the rate of chirping tends to increase as well. This relationship can be described and quantified through statistical analysis.

4. What are some potential limitations of statistical analysis of chirps and temperature?

One limitation of statistical analysis of chirps and temperature is that it can only determine a correlation between these two variables, but cannot establish a causal relationship. Additionally, the data used for analysis may not accurately represent the entire population, which can affect the validity of the results.

5. How can the results of statistical analysis of chirps and temperature be applied in real-world situations?

The results of statistical analysis of chirps and temperature can be applied in a variety of ways, such as predicting the behavior of certain animal species in response to changes in temperature, identifying potential climate change impacts on wildlife, or developing more effective temperature monitoring systems for wildlife conservation efforts.

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