Share the results

There are a few key steps to reporting the results of statistical analysis. The first is to state the purpose of the analysis and the hypotheses that were tested. The second is to describe the population and sample that were studied, as well as how data were collected. The third is to present the analysis results, including descriptive statistics and any tests of significance that were conducted. Finally, the implications of the findings should be discussed.

Appropriate layouts are suited to meet the required work outcome.

In other words, the appropriate layout may be less complex if the required work outcome is to provide a summary of average ages. If the required work outcome is to provide an estimate of costs in different categories, a more complex spreadsheet may be required.

Typically, a written report includes:

• an overview of the work outcome or question you are trying to answer
• information about the data and what you used to hypothesise
• appropriate visuals
• the results of your analysis
• conclusions
• recommendations.

Supplementary documents like spreadsheets may be attached as appendices to support your recommendations.

Several types of visual aids are used in statistical modelling and reporting.

Some examples appear below.

Graphs

Graphs show the relationship between variable quantities on a pair of axes at right angles.

Line graph

Line graphs are a type of graph used to display data over time. They're created by drawing a line connecting the points that represent the data. Line graphs can be used to track changes over time, compare different data sets, or show how one variable affects another.

Some examples are included below.

To interpret a line graph, start by looking at the title and axes to see what the graph is about and what units are being used. Then, look at the overall shape of the line to get an idea of the general trends. Finally, look at specific points on the line to see if there are any notable changes.

Keep in mind that line graphs can sometimes be misleading. For example, a steep line might make it appear that there is a large change happening when there is only a small change. Carefully examine all aspects of the graph before drawing any conclusions.

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Bar graphs

Bar graphs consist of a set of data points arranged in an x-y coordinate system where the height of each bar represents the magnitude (value) or frequency of the data. The main purpose of a bar graph is to make it easy for the reader to see comparisons between different data points. For example, if you were looking at the sales figures for two different products, a bar graph would make it easy to see which product was selling better.

Another common use is to show trends over time. Bar graphs can also be used to show relationships between different variables. For example, you could use a bar graph to show how the price of a product affects its sales.

When looking at a bar graph, there are several things you should consider to interpret it correctly. First, look at the scale on the graph and note the range of values it covers. This will give you an idea of how large or small the bars are in relation to each other. Next, look at the labels on the x- and y-axes to see what information is being represented. Finally, look at the title of the graph and any other information provided to understand what the graph is trying to show.

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Charts

Charts can be used to compare data points. For example, a bar chart can be used to compare the sales of two products side by side. This is helpful when trying to decide which product to invest in or which company is performing better overall.

Charts can also show relationships between data points. For example, a scatter plot can be used to show how two variables are related. This is helpful to understand things like cause and effect or how one variable affects another.

Pie

Pie charts are used for a variety of different statistics. They can show how much of something is in a whole, how much each part makes up of the whole, and how it has changed over time. Pie graphs can be used to compare data between two or more different things. They are also very easy to understand because everyone knows what a pie is.

To interpret a pie chart, look at the entire picture. What do the slices add up to? This will give you a good idea of what the overall data looks like. Once you've done that, you can start to look at individual slices. Compare each slice to the others and see if there are any outliers.

Scatter plot

Scatter plot charts are used to display the relationship between two variables. The axes represent the two variables, and points are plotted on the chart according to the values of the two variables.

Scatter plot charts are often used in statistics to determine whether there is a correlation between two variables. If there is a correlation, then the graph will be linear. If there is no correlation, then the graph will be nonlinear.

To interpret a scatter plot chart, look at the position of the dots on the chart. If the dots are close together, it means that there is a strong relationship between the variables. If the dots are spread out, it means that there is a weak relationship between the variables.

Histogram

A histogram is a graphical representation of frequency data. It is used to display the distribution of data and to help identify the shape of the distribution. The purpose of a histogram is to provide a visual representation of how often values occur in a dataset. Histograms can be used for statistics, such as determining the standard deviation or median or for finding outliers.

To interpret a histogram chart, start by looking at the x and y axes. The x-axis represents the different bins, and the y-axis represents the number of items in each bin. If there is a lot of variation in the data, you may see multiple peaks on the chart. These peaks indicate where the most items are concentrated.

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Diagrams

The purpose of diagrams is to visually represent information. Diagrams can be used to show relationships between variables, to illustrate a process, or convey information concisely.

Diagrams are a powerful tool for visualising information.

Tree

The tree diagram is a graphical representation of the hierarchical relationship between items. It is used for both statistical and common purposes. The most common type of tree diagram is the family tree, which maps out the relationships between family members. Other common uses of the tree diagram include organisation charts, product hierarchies, and food webs. A tree diagram is a valuable tool for visualising data because it displays information in a clear and concise manner.

To interpret a tree diagram, start at the root node and work your way down to the leaves. Each node in between represents a step in the process, and the links between nodes represent relationships between items.

Venn

A Venn diagram is a graphical representation of the relationships between two or more sets of data. The purpose is to visually display the similarities and differences between the data sets. Venn diagrams are often used in business and marketing to compare and contrast customer groups, products, or services. They can also be used in research to compare and contrast data sets.

They are created by overlapping two or more circles, with each circle representing a data set. The area of overlap between the circles represents the similarities between the data sets, while the non-overlapping areas represent the differences.

To interpret a Venn flow chart, look at the overall shape. Is it symmetrical? Asymmetrical? How many overlapping areas are there?

Next, look at the size of each section. What do the different sizes represent?

Finally, look at the labels on each section. What do they represent? What appears in both sections?

Flowcharts

In statistical analysis, flow charts can be used to visualise data sets, relationships between variables, and patterns.

Network

Network flow charts are a type of statistical report that visualise the flow of information between nodes in a network. By understanding how information flows through a network, businesses can optimise their operations to ensure maximum efficiency.

To interpret a network flow chart, start by identifying the source and destination of the data flow. Then, trace the path of the data packets as they travel through the network. Pay attention to areas where there is a high volume of traffic, as this may indicate a bottleneck.

Cluster

A cluster flow chart is a type of flow chart that is used to illustrate the relationships between different clusters or groups of data. Cluster flow charts are often used to show how data is distributed across different groups or to compare the similarities and differences between those groups.

To interpret a cluster flow chart, consider what type of data is being represented. Each circle on the chart represents a group of data points, and the lines connecting the circles represent the relationships between those groups. The size of each circle corresponds to the number of data points in that group, and the width of the lines corresponds to the strength of the relationship between the groups.

Tables

Column

Column tables are one of the most important tools used in statistics. They are used to organise and display data in a way that is easy to understand. Column tables can be used to compare data, find trends, and make predictions.

They can also be used to compare two sets of data or to compare data over time. If you were looking at the number of hours worked per week by employees in a company, you could use a column table to find out whether there was an overall trend of increasing or decreasing hours worked.

To interpret a column table, you need to understand what each column represents. The first column is the dependent variable, and the other columns are the independent variables. The dependent variable is the variable that is being predicted or explained by the other variables in the table. The independent variables are the variables that are used to predict or explain the dependent variable.

The second column in a column table is the predictor or explanatory variable. This is the variable that is used to predict or explain the dependent variable. The third column is the response or outcome variable.

One or two grouped

Tables can be created with one or two variables. A single variable table is a table that shows the distribution of a single variable. The variable can be anything that can be measured, such as age, income, or height. The table will show how many people have each value of the variable, for example.

To interpret a single variable table, look at the distribution of the values. This will tell you how many people have each value and how spread out the values are. You can also look at the mean and median to get an idea of where most of the values lie.

A one-variable data table appears next.

A two-variable table would compare the data points and show how they are related. Two-variable tables are often used in statistics to show the relationship between two variables.

A two-variable table appears next.

Financial reports are critical documents for any business. They provide a snapshot of the company's financial health and performance over a period. It is important to know how to file and store these reports in a secure and confidential manner.

There are a few steps to follow when filing and storing financial reports. First, make sure the data is secure. This means keeping the physical documents in a safe place where only authorised personnel can access them. Second, maintain confidentiality by ensuring that only those who need to see the reports have access to them. Lastly, establish a process for regularly reviewing and updating the reports so that they are accurate and up to date.

By following these simple steps, you can ensure that your financial reports are properly filed and stored in a secure and confidential manner.

Conclusion

In conclusion, financial statistics are powerful tools that can be used to interpret and understand various aspects of business performance. By reviewing a company's financial statements, and other data, analysts can identify trends and make predictions about the future and compare companies in the same industry. By understanding financial statistics, investors can make informed decisions about where to put their money. 

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Watch the video to reinforce the key steps if required.