# Collecting and merging the data from the Office fo

## Collecting and merging the data from the Office for National Statistics (the UK), or other international (e.g., UNCTAD or WB), industry (e.g., Statista,com) and firm-level databases (Fame and Compustat).

The primary theme of the paper is Collecting and merging the data from the Office for National Statistics (the UK), or other international (e.g., UNCTAD or WB), industry (e.g., Statista,com) and firm-level databases (Fame and Compustat). in which you are required to emphasize its aspects in detail. The cost of the paper starts from \$299 and it has been purchased and rated 4.9 points on the scale of 5 points by the students. To gain deeper insights into the paper and achieve fresh information, kindly contact our support.

Element 011 – COURSEWORK (70%) Statistics

Individual 2000 word statistical report.

Description of assignment

The main challenge is to identify the topic of true interest for yourself for the data analysis. Keep in mind that you can this assignment will give you a chance to work on the topic for your dissertations and develop a strong background for the data analysis.

You have a full freedom in selecting the topic, which may span from comparing international economies and markets (IBM students), looking at the national development, global and local industries, or even individual firms. You are most welcome to discuss your topics and ideas during the tutorials or beyond scheduled classes.

You will collect the data from the official statistical sources and the firm-level databases, and use statistical exercises conducted in the seminars as a basis for your analysis. The methods I would like you to practice in this assignment will follow the five steps:

Step 1: Collecting and merging the data from the Office for National Statistics (the UK), or other international (e.g., UNCTAD or WB), industry (e.g., Statista,com) and firm-level databases (Fame and Compustat).

Step 2: Calculating descriptive statistics for the populations you are studying: frequencies, measures of central location, and dispersion.

Step 3: Calculating correlations among relevant variables in your dataset, and

Step 4: Time-series analysis, calculation of probabilities or inferential analysis using appropriate t-tests or analyses of variance - .

Step 5: Reporting using the guidelines of the UK Statistics Authority.

The expected outcome of this assignment is: (1) Excel file with the collected data and calculated statistics, and (2) a 2000 word write-up of the process you followed in and findings from your analysis following the guidelines of the UK Statistics Authority.

Task: Study your dataset using descriptive statistics and visualization methods in Excel, Tableau and SPSS. Note down any anomalies, outliers, or extreme skews or multimodalities in your distributions that you can identify using these methods.

Step 3. Correlations
Next you will study how the scales and items in your data might correlate with each other. The goal of looking at correlations is to identify relationships between your measurements and suggest possible causal relationships.
The most common measure of correlation between variables is “Pearson`s correlation” calculated by dividing the covariance between the two measures by the product of their standard deviations. This operation creates an r-value (Pearson product-moment correlation coefficient), ranging from -1 to 1. However, you cannot make a
conclusive statement on the relationship between these variables simply by looking at the r-value, because the r-value is extremely sensitive to the data distribution and population size. Therefore, you are expected to conduct a significance test to whether a correlation is significant given its data distribution and population size.
Excel provides methods to calculate correlations and significance tests.

Task: Identify correlations among your scales using Excel or SPSS. Report high correlations with r-values and p-values.

Step 4. Inferential Statistics
The final data analysis step in this assignment is to test hypotheses about your data using inferential tests. You will be using these tests to identify how your categorical variables affect your scales or response variables. As it will be discussed in class, what inferential test you should be using will depend on your data design. At the lectures we will discuss a decision map, which will help you choose the appropriate test for your dataset. At the computer workshops you will learn a list of functions that you can use to conduct these tests.

Excel provides all the tools you will need to conduct inferential tests.

Task: Choose the appropriate inferential test based on your experimental design using the decision map. If necessary, conduct post-hoc comparisons across conditions. Create bar graphs to visually support your results. You can use the Excel functions described in the lectures and computer workshops.

Step 6. Reporting using statistical standards

Quick reference to the guidelines of the UK Statistics Authority: