Tag: Skewness

Using the Analysis Toolpak, present the correlation coefficient between Age and Pain Score.Is it high or low? Is it positive or negative? Is it what you were expecting to be?Explain your answer.

Descriptive Statistics

Provide your answers in an Excel file. Any questions that ask for explanation can be included in a separate tab within the same Excel file.

Using this, provide the mean age of those patients visiting the ED in the United States in
2016.

Using the Data Analysis ToolPak, provide the descriptive summary of the “Age Variable” including mean, median, mode, minimum, maximum, age, skewness,Dariance and standard deviation. Describe your results in 3-4 sentences.

Perform a descriptive summary of the “Pain variable” including mean, median, mode,minimum, maximum, age, skewness, variance and standard deviation. Describe your results in 3-4 sentences.

Using the IF function (nested IF), classify the pain variable into three categories
a. Mild if pain score is between 0 and 3
b. Moderate if pain score is between 4 and 7
c. Severe if pain score is between 8 and 10.

Using the COUNTIFS function, create a cross-tabulation with gender and pain categories
[Mild, Moderate and Severe].
Cross Tabulation between gender and pain categories. Present the frequencies and the percentages. Describe your cross-tab in 4-5 sentences.

Using the Analysis Toolpak, present the correlation coefficient between Age and Pain Score.

Is it high or low? Is it positive or negative? Is it what you were expecting to be?Explain your answer.

Present a scatter plot to show the correlation between Age and Pain.

Provide two sets of variables in the dataset might you be interested in seeing a relationship? Explain why?

Find the variance, standard deviation and standard error, skewness and kurtosis for RW, ORA and SF data sets. Describe and compare the skewness and kurtosis for the three data sets. What do you notice?

Math/Physic/Economic/Statistic Problems

The following data is provided about the number of species spotted in the whole area of a specific reserve and in a specific small forest that is a part of that reserve.

The table below provides a breakdown of the species spotted.

Small Forest (SF)

Name Number

Species 1 0

Species 2 23,228

Species 3 56,252

Species 4 202,913

Species 5 492,103

Species 6 1,701,090

Species 7 1,262,898

Species 8 919,113

Species 9 386,912

Species 10 194,489

Total 5,239,030

Reserve – Whole Area (RW)

Name Number

Species 1 0

Species 2 24,120

Species 3 60,028

Species 4 220,182

Species 5 539,691

Species 6 1,856,706

Species 7 1,377,018

Species 8 1,004,087

Species 9 423,505

Species 10 210,716

Total 5,716,053

Using these data provided answer the following questions:

1.a) Create a table that shows the percentage contribution of each species to the total number spotted for the Reserve as a whole (RW) (e.g species X accounts for 3.71% of the total RW species number).

b) Create a table that shows the percentage contribution of each species to the total numbers spotted for SF (two decimal points needed).

c) Compare which species contribute more to the total numbers of species in RW and compare them the ones for SF?

2. Create a new data set that will include the values for the species spotted in RW but not in the SF area.

Create a table like the ones provided with these new data set and name it ORA (other reserve areas), and calculate the percentage contributions as in question 1.

3. Find the minimum, maximum, range, median and mean average for RW, ORA and SF data sets (not for the percentages worked in question 1 but for the absolute values like the ones given in the original tables and the one you calculate in question 2). Compare the mean average of the three groups. What do you notice?

4. Create three different graphs for the 3 different data sets (RW, ORA and SF) showing the Species name on x-axis and the number spotted on y-axis.

Create a combined graph showing the Species on x-axis and the number spotted on y-axis for all data sets. Which one do you find more useful and why is that?

5. Find the variance, standard deviation and standard error, skewness and kurtosis for RW, ORA and SF data sets. Describe and compare the skewness and kurtosis for the three data sets. What do you notice?