Question

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What is the difference between training data sets and test (or testing) data sets?

Training data is existing data that has already been manually evaluated and assigned to a class.  You will use this data to train your model to predict what class your data falls into given what they have in common. Testing data is simply that, small amounts a data that you use to determine if your model does indeed work. You will compare your test data to your training data outcomes to see if your model is likely to determine the correct class.

Explain exhibit 4-2 and why there four dimensions are helpful in describing information to be communicated? Exhibit 4-2 list conceptual and data driven as being on two ends of a continuum. Does that make sense or can you think of a better way to organize and differentiate the different chart types?

Exhibit 4-2 helps you determine what kind of data you are presenting and the best means to present it to stakeholders. The exhibit shows that there are four different types of data you can present, and are spit into quadrents. In the left quadrants you will find Nominal data, which is the simplest form of data. Some examples (as provided from the text) are hair color, gender, and ethnic groups. Some other examples could be eye color, affiliated religion and Month of Birth. This is the kind of data that you cannot rank or average and cannot have a mean or median.. Other qualitative data that you will find in the left quadrants is ordinal data.   Ordinal data is similar to Nominal data, except that it can be ranked, a provided example wold be student grades as A, B, C, D or F. Nominal and Ordinal data can be grouped and it's value is often found in proportions. For example, 20% of students earned a D or lower, or, 45% of accounting students are male. Quantitative data is found on the right side quadrants is more complex than qualitative data, because not only can it be gouped and sorted, but the differences in the data have value. Quantitative data is comprised of two types of data which are interval and ratio, although many would say that there are little difference between the two. Quantitative data can be further categorized as discrete data, which is represented by whole numbers and continuous data, which can be any value within a range.

The upper quadrants of the chart are declarative which is where you might present (declare) your findings. The lower half is called the exploratory, which is often used to explore your findings if you have not already answered your question.

I cannot think of a better way that would help you organize data to present it. This exhibit considers they types of data you con be working with, and whether or not you will have a definitive answer two your question or wish to explore further.

According to exhibit 4-8 which is the best chart for showing a distribution of a single variable, light height? About hair color? Major in college? The best chard for showing a single variable like height would be a bar chart. Hair color might be better represented as a pie chart. Major in college might be a represented by a word cloud, which is a neat way of emphasizing popular degree fields, or simply as a bar chart, if you wnat to convey data simply.

Answer 1

Your response should be that: Yes all your information is absolutely correct but still you can convey it in much simpler form .You can also use some diagrams to convey it easily.