FNS60217 - Interpret And Use Financial Statistics And Tools - Tafe Assignment Help

Assignment Task

Task A:

1.    Describe the sampling technique you have used and explain why you used this particular technique (your response should be between 100 – 200 words).
2.    Choosing an appropriate number of class intervals and class widths, report your data using a grouped frequency table. Plot the distribution in a histogram and comment on its shape, using appropriate technical terms.
3.    Add a cumulative frequency column to your frequency distribution. Draw a cumulative frequency histogram and polygon of the data.
4.    Calculate the mean, standard deviation and standard error of the number of sick leaves, for your 1.5 years of monthly data – use descriptive stats.
5.    The bank believed that the average number of sick leaves during the month were 53. Using the variables calculated above (4) conduct a Hypothesis test to see if the average number of sick leaves during the last 1.5 years is significantly less than 53.
 

Task B:

1.    Obtain a scatter-plot of the monthly number of sick leaves vs psychologist sessions per month.  Think carefully about which variable should go on the vertical axis – remember, it is the independent variable that goes on the horizontal axis (i.e. the x-axis).  Make sure you label your axes properly and your graph has an appropriate title.  Briefly describe the nature of the relationship between these two variables (your response should be between 100 – 200 words).
2.    Using Tools>Data Analysis in Excel carry out a regression analysis on these two variables.  Copy the output into your assignment and use it to determine the following:
a.    Write down the regression equation
b.    State the R-Square value and the Standard Error and explain what they mean with respect to this data.
c.    Write down the value of the gradient of the regression line and explain what it means in this case.
d.    Is the constant or intercept value significant in this case?  How do you know this?
e.    Briefly explain why you think this regression model is, or is not, a good model.

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