Data interpretation download

The varying scales include:. For a more in-depth review of scales of measurement, read our article on data analysis questions. Once scales of measurement have been selected, it is time to select which of the two broad interpretation processes will best suit your data needs. When interpreting data, an analyst must try to discern the differences between correlation, causation, and coincidences, as well as much other bias — but he also has to consider all the factors involved that may have led to a result.

There are various data interpretation methods one can use. The interpretation of data is designed to help people make sense of numerical data that has been collected, analyzed, and presented. Having a baseline method or methods for interpreting data will provide your analyst teams with a structure and consistent foundation. Indeed, if several departments have different approaches to interpret the same data while sharing the same goals, some mismatched objectives can result.

Disparate methods will lead to duplicated efforts, inconsistent solutions, wasted energy, and inevitably — time and money. In this part, we will look at the two main methods of interpretation of data: a qualitative and quantitative analysis. Qualitative data analysis can be summed up in one word — categorical. With qualitative analysis, data is not described through numerical values or patterns, but through the use of descriptive context i.

Typically, narrative data is gathered by employing a wide variety of person-to-person techniques. These techniques include:. A key difference between qualitative and quantitative analysis is clearly noticeable in the interpretation stage. As person-to-person data collection techniques can often result in disputes pertaining to proper analysis, qualitative data analysis is often summarized through three basic principles: notice things, collect things, think about things.

Quantitative analysis refers to a set of processes by which numerical data is analyzed. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median.

Typically, quantitative data is measured by visually presenting correlation tests between two or more variables of significance. Different processes can be used together or separately, and comparisons can be made to ultimately arrive at a conclusion. Other signature interpretation processes of quantitative data include:. Now that we have seen how to interpret data, let's move on and ask ourselves some questions: what are some data interpretation benefits?

Why do all industries engage in data research and analysis? The purpose of collection and interpretation is to acquire useful and usable information and to make the most informed decisions possible. From businesses to newlyweds researching their first home, data collection and interpretation provides limitless benefits for a wide range of institutions and individuals.

Data analysis and interpretation, in the end, help improve processes and identify problems. It is difficult to grow and make dependable improvements without, at the very least, minimal data collection and interpretation. What is the keyword? Vague ideas regarding performance enhancement exist within all institutions and industries. Yet, without proper research and analysis, an idea is likely to remain in a stagnant state forever i.

So… what are a few of the business benefits of digital age data analysis and interpretation? Informed data decision-making has the potential to set industry leaders apart from the rest of the market pack. Most decisive actions will arise only after a problem has been identified or a goal defined. Data analysis should include identification, thesis development, and data collection followed by data communication.

If institutions only follow that simple order, one that we should all be familiar with from grade school science fairs, then they will be able to solve issues as they emerge in real-time. Informed decision-making has a tendency to be cyclical.

This means there is really no end, and eventually, new questions and conditions arise within the process that needs to be studied further.

The monitoring of data results will inevitably return the process to the start with new data and sights. The insights obtained from market and consumer data analyses have the ability to set trends for peers within similar market segments.

A perfect example of how data analysis can impact trend prediction can be evidenced in the music identification application, Shazam. Users make 15 million song identifications a day. With this data, Shazam has been instrumental in predicting future popular artists. When industry trends are identified, they can then serve a greater industry purpose. Many times, Statisticians may use exact figures against these sectors inside or outside as the case may be.

In this section, data is represented as horizontal or vertical bars. One of the parameters is given on the x-axis and other on y-axis.

Here we need to understand the given information and thereafter answer the given questions. A bar graph or a bar chart that presents the grouped data with the help of rectangular bars.

These bars are either horizontal or vertical and their lengths are proportional to the value that they represent. There are two axes in the graph in which one represents particular categories being compared and the other axis shows a discrete value. Those bar graphs in which clustered groups of more than one bar are presented are known as grouped bar graphs, And, bar graphs in which bars are divided into sub parts to show cumulative effect are known as cumulative bar graphs or stacked bar graphs.

A line graph shows the quantitative information or a relationship between two changing quantities with a line or curve. We are required to understand the given information and thereafter answer the given questions.

A line graph or a line chart is a geographical representation of the change in two variables over a period of time. A line graph is created by connecting various data points. Each data point is obtained as a result of plotting a point when we are given the value of two variables such as one independent variable and one dependent variable.

Line graphs are a small but important part of data interpretation. In line graph questions, candidates are provided with certain data in the form of a line graph. The data may be related to various categories such as the following, Average income and expenses, Comparing pie charts, population or demographics study, demand and supply, funds, distribution and utilization etc. Know about Line Chart Data Interpretation here.

In Caselet DI, a long paragraph is provided and with that as the basis, some set of questions are asked. We need to understand the given information and then answer the given questions. Candidates can find different tips and tricks from below for solving the questions related to Data Interpretation.

Tip 1: Read the entire question carefully — Read the complete data given in the form of values, graph etc. Tip 2: Analyze the data — Take a look and analyze the data carefully. Tip 3: Pay attention to the units — Many times, different units are used in one question. Tip 4: Use of approximation — If the options are adequately far apart then you can approximate values, fractions and percentages to nearby numbers which can ease our calculations. Tip 5: Use of last Digit — Check if all options have different last digits then to find the correct option we can just calculate the last digit of our answer but then approximation is not at all allowed.

Tip 6: Mental calculations — Try to do mental calculations as frequently as possible while practicing. It will help in minimizing the time to solve the question. Question 1: Directions: Study the following information carefully and answer the given questions based on it. Find the respective ratio between the number of neem trees planted in the year and the number of banyan trees planted in the year Question 2: What was the approximate average number of neem trees planted in all the years together?

Question 3: How many percent more teak trees planted by the government in the year as compared to ? Question 4: Directions: The following Pie chart shows the percentage of students who like five different subjects of engineering from college x. Percentage of students who like 5 different subjects of engineering. Total number of students in college x is Question 6: Directions: Study the given graph and answer the question that follows. What is the ratio of the total daily sales of newspaper P in cities A and C to the total daily sales of newspaper Q in cities B and D?

IBPS Guide. Data Interpretation PDF free download questions are here. DI is one of the highly covered topics in the quantitative aptitude section. It is common for both the preliminary and mains test. The difficulty level of the questions though varies for both phases. So, prepare with the data interpretation pdf questions and approach the exams without fear. These contain different types of data interpretation Pdf free download questions ranging from prelims to mains level.

Candidates are advised to practice them thoroughly to ensure selection in the upcoming banking exams. Data Interpretation PDF practice questions are here.

Data Interpretation DI is an important part of all bank exams. We provide you data interpretation pdf practice questions with answers and explanations.

This data interpretation pdf with the solution will be convenient for your preparation. If you do not understand any concept, you can clarify them with the solutions.