Sampling Your Population-One Nut at a Time!

Sampling is a little like going to the grocery store and plucking a nut or two to "sample" the product. While this might get you kicked out of your local grocery store in a research world it is encouraged to sample as much as you want!!!! No one will shun you for grabbing a handful of sample nuts as long as you share what you did! 🤯

It would be in most cases, except a few small populations, excruciatingly difficult to test everyone in the population. We then must consider a smaller and more reasonable size that "sort of" shared the same characteristics as the main population.

The risk in many of these cases is that sampling is done incorrectly and misrepresents the true population. To better ensure accuracy we may use a number different methods such as random and convenience samples. The video below gives a few ideas....




There is no such thing as an accurate sample! You can sample as much as you like, over and over, and it won't be 100% correct! Sampling in different ways by taking multiple measurements from different areas leads to better outcome.

Sometimes samples are not big enough to draw any real conclusions. Confidence levels and sample size calculations can help ensure a size of participants needed to make meaningful conclusions.

Likewise, how we design our study is going to have influence on the samples taken. Designs will impact how and what types of samples are needed and where we draw them from.

What we should learn here is that sampling is very important and if we desire to have studies that draw meaningful conclusions from the data some consideration over sampling is needed. Review your study design, access to samples, the selection and tools you will need to make a solid analysis of your study focus.

Data!!! Data!!! Checking on Secondary Data Sources!

Data can come from all types of sources and piles up in our dashboards and can be of great help or hindrance to the achievement of our goals. If the data isn't managed properly you can make fatal errors that can destroy your business or cost you a lot of money down the road. Because research is expensive most people rely on secondary sources. Secondary sources are cheap but do require a level of care to ensure the data is saying what you think it is saying.

Let us start by saying that secondary data can be expensive! There is a reason why secondary data makes more sense versus inventing and conducting your own research. It can be expensive and time consuming to create new studies. If you don't have the expertise in your business you will likely need outside consultants.

Those businesses that rely on secondary data may want to consider a few issues.....

1. Make sure the data fits your purposes. Secondary data may or may not meet your needs. Just because someone counted the amount of cars it may have no relation to the type of radio those cars use.

2. Check the sources of data. Yes...you need to read the fine print! How the data is collected, organized used and managed is key to deter validity for your study.

3. Look for similar type studies that may support or not support the data collection methods of the study.

You would be amazed but there are times when studies look to create a biased result. This can often happen in political or corporate arenas where a specific outcome has consequences. Academic and government data is more likely to be non-biased when compared to corporate research.

4. Look for non-profits, government, and others who collected data and have a stake in accurate information.

Sometimes the secondary sources are not enough and you must try and build your own knowledge on an ideas. Surveys are often used to help gauge opinions about services and needs. While surveys are generally easy to build if you ask straight forward questions there are all types of caveats and mistakes you can make when you don't have "in house" scientific knowledge. The best bet is to use experts when you plan on using the information for significant investments.

Here is a little advice when determining in house or secondary sources. First try and use secondary sources that provide contextual information about the problem. If there the available information doesn't necessarily answer your question consider an in-house study. Be very sure the answer is worth the time and expense. If you are gauging your customers opinions in a small business just ask them what you want and take notes. If you are poling 20K customers you may want to have someone look at your survey and delivery methods before proceeding.

Industry-Curriculum Alignment Through Skills Assessment

It was great to work with my colleagues presenting a project started a while ago. We found a way to assess market readiness of graduates by using market research mixed with current assessment practices. The methodology worked great for something new! Will likely discuss a little more in the future. :)

Chewy Outdoor U.P. Adventures-Thoughts from a Dog :)

Not sure where he taking me but I hope there are treats!

I know this is silly but I can't keep talking about wildlife, hiking and stuff over and over so I thought I would spice it up a little with thinking about hiking from a dogs angle.....

This is Chewy! He is a sock thief and a convicted potty violator. Despite his shortcomings he loves the outdoors.

We try hunt, hike, cross country run, snow shoe and other stuff as much as we can. This little guy can jump in the water and play around as much as the big dogs.

Must have been an elephant path.

Today's adventure was hiking back on some ATV trails in search of fitness, outdoors, and maybe some small game.

Supporting wild life, habitat restoration, sustainable hunting, pollution clean up, and a lifestyles that allows for outdoor activities is helpful to our lives. There is a part of us that must reach back to our natural state every once in a while to feel more at ease. This is one of the reasons why I love the Upper Peninsula of Michigan!

Refreshing water to drink.

Every time I put one in my mouth I get yelled at!

You can read a little about the U.S. Wildlife Services to learn about what they do. You pay their service through our tax dollars so understand where your money is going and how it helps our environment. https://www.fws.gov/habitat/

Discovering Problems with Exploratory Research

When we think of research an image comes to our mind of the lab coat professor going over calculations, long formulas and test tubes to come up with the next greatest discovery. No need for the coke bottle glasses that move into the finite details of "fineness". Exploratory research may ask a question but doesn't necessary seek a specific answer. Its main goal is to get into the weeds to understand the inner workings of their subject without coming to an pre-conclusions.

Exploratory Research:

When you are not sure exactly what is going on but you got a solid "hunch" you may want to explore ideas and concepts to better understand a problem. It focuses in a broad area and continues to adjust and changes as the situation changes. It is possible to start with one understanding and end with a completely different one later on.

The essential purpose of exploration is to go into the unknown and explore what seems to be an appropriate path of discovery. You really don't know what to expect and instead allow elements to go forward unimpeded so that you can start to see some relations between elements in a way that leads to future research.

Description of Occurrence.

As you explore ideas and concepts you want to include as much descriptive detail as possible. Because you don't know what the elements are you want to record as much pertinent information as you can so as to further your analysis. Sometimes things that seem important today are not so important tomorrow. At some other time you very well may find the opposite to be true.

Describing what is occurring and taking proper notes, recordings, and other documentation helps in the overall evaluation down the road. You will want to document any study you have conducted from start to finish. There should be some logic and method you are following throughout your work and the type of documentation will relate to your design.

There is no Causality in Exploratory Research

There is no causality in exploratory research. We don't know what the variables are but have an idea of where to look for them. While you may end up making some inferential judgments about causality the strength of those connections and whether they are relevant relies on a more quantitative approach.

Don't go into the research with a lot of pre-beliefs and bias or the directions you take will end up leading to false conclusions. The goal is to find new associations among ideas and concepts and not necessarily to prove that existing one's exist. Time again and again the bias of the research makes it into what they are discovering.

Why its not like a Lab?

In a lab you can design studies that manipulate variables. In the field the variables are at the mercy of their environment making cause and effect much more difficult to determine. Exploratory research allows one to determine potential connections while quantitative determines the strength, or insignificance, of those connections. 

First Snow in the Upper Peninsula

The first snow is one of the most beautiful. White, fluffy, soft with a dusting on the tree tops. With pristine beauty comes a price. You must make the effort to get out and see it! There are miles upon miles of hiking and hunting trails in the Upper Peninsula of Michigan just waiting for you to explore. When you need to get out of the city and into nature to gain peace of mind head north!  These pics were taken on Days River. I'm pretty sure "Chewy" my dog is wondering whether he has some husky blood in him. 😮

Market Research as a Process and Decision Making Tool

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Market research allows companies to understand the market and what types of products and services have value for revenue generation purposes. Without this knowledge companies are blind making intuitive judgement about things they don't really understand. That works great when your company is small and doesn't have a lot of capital. Exploratory behavior can make a big difference, but when companies are big and there are investors involved it makes more sense to have a scientific understanding of the market. Science can give you a road map.

When I used the term "scientific" I don't necessarily mean it has to follow the highest level of scientific scrutiny. I have some colleagues that will disagree with me because they are scientific purists. Something simple like a survey needs 3 years of preparation and contextual literature review. Don't forget validation! Silly!

If you are trying to change public policy with a survey you should go through all of the steps...but if you are simply trying to gain some understanding of what your customers want then you might be ok asking straight forward questions. Conducted in the right way gracious customers will give you more information than you want or need.

A problem arises when we want to justify the answer through a line of research. In our head we believe we know what the study will tell us and in turn subconsciously design the questions that give us the answers you seek. I see people do this in their everyday conversations when they have a point to make and skip over all the logic. The conclusion is not justified in the least! Leaving out important information, framing things incorrectly, designing leading questions, etc...all lead to biased results.

What you measure will also determine what results you get so make sure you are get into the details. Read this article on digital economy and its influence, or lack thereof, on GDP calculations (Click Here). If your really really really motivated you can read the full study and understand the studies design and what it truly indicates (Click Here) You will see that the way we calculate things can have some serious economic consequences.

How that data is collected and processed determines the overall value of the outputs. This is one reason why studies have limitations. It can't be everything to everyone and the inherent design of the study creates limitations! You should be well aware of what they are before you collect data!

Designing strong studies that have internal validity are important in the overall process of understanding the market and creating some predictive modeling. Be sure you know what you want to measure, do your background research and design the study in a way that leads to answering that specific question. If your lucky you can create a model and apply that to other places.

Sometimes you must complete preliminary research to ask the right questions. You think it would be easy but it really isn't. Having a general sense of the problem but might need to explore the idea a little to define it specifically for a research question. This research question becomes the basis for everything else within the study. Your single focus is/are to answer this question (s).

You will find as you begin to collect the data that it can start getting jumbled up and you will lose track of what you are trying to accomplish. Data is the source of all experiments and you might want to find some way of taking in that data, analyzing it, manipulating the variables, etc... Consider that collection may require specialized equipment or round about ways of getting the information while the encoding and analyzing of that data is more statistically oriented.

Once you have this mountain of data and it has been scrubbed and categorized there will be a need to analyze that data. The type of analysis you do will depend entirely on what you want to accomplish and what type of data you have. Some scientists want you to conduct huge analysis for a survey. In the business world you used what is most prudent and provides the most useful data. Statistics, regression analysis, etc.... is a little too complex for this discussion.

Three points of key advice:

1. Define your problem as everything revolves around this.
2. Design your study to ensure it is measuring what you say it is measuring.
3. Ensure you collect and encode data properly so as to create a stronger analysis at the end.