Please tell me where the information I'm providing on my worksheet is NOT meeting the criteria of the checklist. I asked the professor for some specific insights on where my answers/info is NOT meeting the criteria and his only response was 'get a tutor'. Below is the checklist and my completed assessment.

MM305M1 Competency Assessment Example

Visit the dataset link to view the datasets that accompany our textbook. Review the dataset titles and select a

data set of interest to you that has at least 30 data values.. See the CA starter video in the LiveBinder.

1) Summarize data with frequency distribution tables.

a) Need a frequency distribution table from the data selected.

b) Need a sentence for each of three findings based on the frequency distribution table in terms of

the variable chosen.

2) Visualize numeric variables through histograms.

a) Using your frequency information construct a histogram (for continuous variables) or bar chart

(for discrete variables). Make sure to title your chart appropriately.

b) Based on this visual representation, does the data appear to be left skewed, right skewed, or

symmetrical. Explain your rationale for the choice.

3) Calculate measures of central tendency.

a) Determine the mean, median, mode, and midrange for the data.

b) Determine if the data selected is left skewed, right skewed or symmetrical. Explain the

rationale for choosing which way the data is skewed.

4) Interpret data with descriptive statistics.

c) Calculate Q1, Q2, and Q3. Explain the the significance for each measure found. In terms these

results, explain the meaning of the interquartile range.

d) Calculate the standard deviation for your data. Describe the range of values that are within 3

sigma of the mean and the impact it has on the likelihood of a value being in that range in terms

of the variable chosen.

My Assessment response to the checklist:

High School Completion + Crime Rate

Qualitative Variables:States

Quantitative Variables:High School Completion, Crime Rates, Violent Crimes, Property Crimes

I have chosen to review the quantitative variable of High School Completions. Quantitative variables are numerical values, such as, counts, percent and numbers. If it can be added, it's quantitative.

1a. Frequency Distribution Table with Relative Frequency + Cumulative % for High School Completions for all States:

Using formulas in Excel, I created the Frequency Distribution Table using the following steps:

Bin represents a way of sorting data. It is also known as a class interval. Each bin contains a range of numbers from the lowest value to the highest. In this case, the lowest number of high school completions equals 69 and the highest equals 91. So I created bins in a range of 10, e.g. 50-59, 60-69, 70-79, etc.

Frequency was calculated in Excel using the complete list of High School Completions data and the bins I created (as described above) and then I created Labels that illustrate the range of values in the bins.

oWith these values in place, I clicked on the Data tab and chose Data Analysis. I then chose Histogram as my option. My Input Range was my complete list of High School Completions and my Bin Range was represented by Bin values. This process returned both a Histogram and a Frequency Distribution Table.

Relative Frequency was calculated in Excel by first finding the Sum of the Frequency column. The relative frequency is calculated by dividing the value in the frequency column by the sum of the frequency column. It returns the value as a decimal and I usd Excel to convert to a percentage.

Cumulative Frequency was calculated in Excel using the Sum function and just adding the relative frequency to the cumulative frequency from the line above. For example, =SUM(C5+D4).

The categorical variable was number of high school completions

There were no less than 60 high school completions for any one state

Greatest number of high school completions occurred between 80-89 times

At a relative frequency of 66%

2a. Visualize numeric variables through histograms:

The Histogram was created in Excel as the result of creating the Frequency Distribution Table described above.

Based on the visual provided by the Histogram, the data appears to be left skewed because there is more data populated to the left. A greater number of high schools experienced <89 completions. The numbers also bear this out because the mean of 82.81632653 is less than the median of 85. A left skewed distribution is sometimes called a negatively skewed distribution because it's long tail is on the negative direction on a number line. There are two main things that make a distribution skewed left:The mean is to the left of the peak. This is the main definition behind "skewness", which is technically a measure of the distribution of values around the mean and the tail is longer on the left (Statistics How To, 2020).

3a. Calculate the measures of central tendency:

Chart represents data found using descriptive statistics from data analysis in Excel:

Descriptive Statistics for the data provided was calculated in Excel by using the Data Analysis option. Descriptive statistics, in short, help describe and understand the features of a specific data set by giving short summaries about the sample and measures of the data (Kenton, 2019).

The mean is 82.54. The mean represents the average of the data values.

The median is 84.5. The median represents the value that sits in the middle of the data set.

The mode is 87. The mode represents the value that appears most often.

The midrange is the average of the minimum and maximum number of high school completions:91 + 69/2 = 80. The data is left skewed as the mean is less than the median.

4a. Interpret data with descriptive statistics:

A quartile is a statistical term describing a division of data into parts. A quartile divides the data into three parts:a first quartile (lower) known as Q1, a second quartile (median) known as Q2 and a third quartile (upper) known as Q3. The quartile breaks down the data into quarters so that 25% of the measurement are less than the lower quartile, 50% are less than the mean, and 75% are less than the upper quartile (Liberto, 2019).

Using Excel formulas, I was able to calculate the Quartiles for the data set of High School Completions for the 50 states using the following steps:

I isolated the list of High School Completions and created a small table to the right representing Q1, Q2 and Q3.

I placed my cursor in the cell I wanted to return the Q1 value

In the Function field, I typed the formula =Quartile.Inc (.Inc = Inclusive). Inside the parentheses I insert the data values to be included. For Example:B2, B51 represents the high school completions data. I then insert a comma which allows me to choose from Q1, Q2 and Q3). I close the parentheses and hit enter which then populates the cell with a quartile amount. I can then drag the formula down to the remaining two cells and I just need to change the 1 (for the quartile) to a 2 and a 3 respectively.

Quartile 1 is equal to 78.25. The first quartile (Q1) is the middle number between the smallest number and the median. It indicates where 25% of the data is to the left of the median.

Quartile 2 is equal to 84.5. The second quartile (Q2) is the median of a data set.

Quartile 3 is equal to 87. The third quartile (Q3) represents the middle between the median and the highest value of the data set. It is also known as the upper quartile.

Interquartile Range is equal to 8.75. The interquartile range (IQR) represents the middle 50%. It is equal to the difference between Q1 and Q3.

4b. Standard deviation:

A standard deviation is a measure of the amount of variation in a particular data set. With this data set, the standard deviation is low which suggests there is not a lot of dispersion in the data or most of the data is close to the mean or average.

The standard deviation from the mean for this data is 5.657611813. This number was calculated as part of Excel's Descriptive Statistics function in Data Analysis.

Using Excel formulas, I was also able to calculate the following:

One standard deviation from the mean = 76.88238819 (Formula: =Mean-Standard Deviation)

Two standard deviations from the mean or Sigma 2 = 71.22477637 (Formula: = Mean-2* Standard Deviation)

Three standard deviations from the mean = 65.56716456 (Formula: =Mean-3*Standard Deviation)

According to the Three Sigma Rule of Thumb, almost all data falls within three standard deviations of the mean. Typically, 68% falls within the first standard deviation, 95% within the second standard deviation, and 99.7% within the third deviation. With a mean of 82.54 for high school completions across all 50 states, the deviations from the mean indicate the majority of the completion rates are very close to the mean and the data is not widely dispersed.