# The Ability of Small Businesses to Do Statistical Analyzes Every Day

Statistical methods of recording and analyzing data will empower any small-business owner by making that business owner independent in determining how to allocate a budget based on income/expense trends. For example, noting what time of the year business may slow down or speed up based on sales. After noting the times, one could then determine what may be the cause and see what they could do about it. Another example of why descriptive and analytical statistics is of importance would be determining if there is an age-biased treatment for certain conditions, or for certain genders.

Using statistical tests one could determine if there is a significance in treatment. To start off, I’ll be describing how using excel and the add-in analysis toolpak is a great tool in practice.

Excel is a computer application that contains cells where a user can input values and manipulate the data inputted through many functions such as addition, multiplication, determining average of the group, determining the standard deviation, and it goes on.

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Another reason why excel is used in small practices is due to its ability to analyze and interpret data inputted. Examples of input data would include patient age, type of treatment, number of visits, visual analog scores, gender, and the list goes on. Any type of characteristic about a patient’s profile can be utilized in determining the best sort of treatment a patient needs. The Analysis Toolpak would serve as the perfect add-in to help in difficult calculations such as z test calculations and ANOVA calculations.

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Below in Figure 1 are small steps of the equations of z-tests and ANOVA.

The Analysis Toolpak also has a feature to create histograms. Those bar graphs can be a great presentation aid when applying for small business loans or to simply address the staff with a certain reason for a change in policy. There is a linear regression function as well. This would be useful when one needs to predict drops in sales during a certain period of the year or an increase in sales due to it being spring/summertime.

Descriptive data is another subset of statistics and can be very helpful to a small business owner. To define “Descriptive Statistics are used to present quantitative descriptions in a manageable form. In a research study, we may have lots of measures. Or we may measure a large number of people on any measure. Descriptive statistics help us to simplify large amounts of data in a sensible way.1” Some examples of what data to collect have been given in the previous paragraph. To continue with that list one could collect data about socioeconomic status, type of insurance, occupation, other associated symptoms, amount of time until the release of the patient, how that patient heard of the business, and the list goes on. Ways on how to use these input values to increase a practice’s value include: setting goals based on predictive values and assessing the goals every 3-4 months, determining which insurance provider is used most often, and adapting financial and documentation policies around that insurance carrier’s expectations, and analyzing responses off of where they were referred from and putting more funds into that method of advertising/prospecting. The real test of properly using these statistical methods is to check up on the progress that is or isn’t made and adapt the business to overcome the presented obstacles.

The next area of statistics that can be helpful to the small business owner is that of probability. With the tools to be able to predict the probability of outcomes, a business owner can use this information to their advantage by noticing trends of money usage, optimal business times, the influx of patients, and so on. Being able to confidently determine when a certain treatment plan may work better for an older individual than a younger individual will only make that physician a better doctor. One way that we have learned to predict outcome measurements is through using linear regression. According to Yale’s statistics course online2, linear regression will attempt to model a relationship by using a best fit line of inputted x and y values and create a new set of y values given new x values. This equation will take the form of the y-intercept form which should be familiar to most of us. Linear regression is a powerful tool which will only help predict future business trends or even patient response to care.

Lastly, to be able to make sure one’s theory about a certain population is true one must verify that their sample population is a good sample of the population being observed. Some statistics such as parametric work under the assumption of a couple of factors. First that the sample population accurately reflects the population being observed, and second the distribution of data is normal. If a researcher or clinician cannot make these assumptions, it is best to use non-parametric methods of analyzing the data.