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Payroll accounting deals with calculations and distributions of employee’s compensations like salaries, bonuses, commissions, overtime pay. It also helps higher level management to make decisions about labour cost.Type of payroll accounting includes −Initial recordings − Records gross wages, employment taxes which are owed to governmentAccrued wages − Records wages owned to employees which are paid later. Readjustments are made after payments.Manual payments − Records when company pays manually for pay adjustments or employee terminations.Steps for payroll accounting includes −To hire employees.Prepare paperwork regarding payments of employees.Pay checks.Record payroll.Steps to record payroll in general ledger are −Record payroll expenses.Record payroll liabilities.Transition ... Read More
The main difference between capital structure and financial structure is that financial structure consists of left hand side of a company’s balance sheet, whereas capital structure consists of long term debt and shareholder’s fund.Capital structure is a part of financial structure. Capital structure does not include short term liabilities, but financial structure does.Importance of capital structure includes −Increase in value of a firm.Utilisation of available funds.Maximisation of return.Minimisation of cost of capital.Solvency/liquidity position.Flexibility.Controlling.Financial risk minimises.Factors determining capital structure are given below −Trading on equity.Degree of control.Flexibility of financial plan.Choice of investors.Capital market condition.Period of financing.Cost of financing.Stability of sales.Size of ... Read More
Capitalisation is combination of owner’s capital and borrowed capital. That means, it tells about total fund invested in a company. Share capitals, debentures, loans etc.Capitalisation is generally classified as follows −Normal capitalisation.Over capitalisation.Under capitalisation.Over capitalisationIn this, profits are not enough to pay interest on debentures and dividends to shareholders over a period of time. That means, amount generated is used to raise capital than required capital, which results decline in rate of returns.Some of the causes for over capitalisation are as follows −High promotion cost.Purchase of assets at higher price.Liberal dividend policy.Over estimation.Inadequate provision for depreciation.Some of the effects of ... Read More
Plotting a function in R is not a difficult task. We can do it simply with curve function but if the function is very complex then it inside curve function might be difficult. It totally depends on the understand of the person who wants to plot the function, if he or she is well versed with the function then it won’t take much time, otherwise it becomes tedious.Example> curve(exp(x),from=0, to=10)Output> curve((x-1)/(x^2),from=0, to=20,ylab="y")Output> curve(((exp(x))^2)/(x),from=20, to=100,ylab="y")Output
Filtering data helps us to make desired groups of data than can be further used for analysis. In this way, accuracy can be achieved and computation becomes easy. Suppose, we have a homogeneous group then to partition that group based on some characteristics the filter function of dplyr package can be used.ExampleConsider the below data frame −> Subject Score df head(df, 20) Subject Score 1 Stats 88 2 Stats 20 3 Stats 49 4 Stats 31 5 Stats 83 6 Physics 29 7 Physics 43 8 Physics 73 9 Physics 28 10 Physics 74 11 Physics 93 12 Physics ... Read More
Especially when the experimental conditions are same then we expect some of the row values for some columns to be the same, it is also done on purpose while designing the experiments to check the fixed effect of variables. If we want to determine the unique rows then it can be done by using unique function in R.ExampleConsider the below data frame −> x1 x2 x3 df df x1 x2 x3 1 1 1 A 2 1 1 B 3 1 2 C 4 1 2 D 5 2 2 E 6 2 2 F 7 2 3 G 8 ... Read More
Sometimes we don’t require the whole string to proceed with the analysis, especially when it complicates the analysis or making no sense. In such type of situations, the part of string which we feel that is not necessary can be removed from the complete string. For example, suppose we have a string ID:00001-1 but we don’t want -1 in this string then we can remove it and this can be done with the help of gsub function.Example> x1 gsub("\-.*", "", x1) [1] "ID:00001" "ID:00100" "ID:00201" "ID:014700" "ID:12045" "ID:00012" "ID:10078" > x2 gsub("\/.*", "", x2) [1] "ID:00001" "ID:00100" "ID:00201" "ID:014700" "ID:12045" ... Read More
We often see mistakes in data collection processes and these mistakes might lead to incorrect results of the research. When the data is collected with mistakes, it makes the job of analyst difficult. One of the situations, that shows the data has mistakes is getting strings in place of numerical values. Therefore, we need to convert these strings to NA in R so that we can proceed with our intended analysis.ExampleConsider the below data frame −> x1 x2 df df x1 x2 1 1 67 2 3 67 3 6 67 4 7 67 5 5 XYZ 6 2 XYZ ... Read More
The combination of two vectors is used for many purposes such as performing two-way ANOVA, presenting data table, or making visual representation of the data. The combinations can be created with many special characters in R by using paste and rep function.ExampleConsider the below vectors Class and Names.> Class Class [1] "Stats" "Maths" "Chem" "Physics" "O-R" > Names Names [1] 101 102 103 104 105Suppose we want to combine Class and Names in a way that the new vector contains Stats|101, Stats|102, and so on. Also, we want to do the same with different special characters.We can do this by ... Read More
Data can be supplied to us in any form but it is possible that it is not the appropriate one that should be used for analysis. Sometimes data is recorded in a data frame but we might need it as a vector. In such type of situation, we have to change the values of our data frame in a vector. This can be done by reading the data frame values by reading them as.vector after transposing the data frame with t.ExampleConsider the below data frame −> x1 x2 x3 df df x1 x2 x3 1 1 1 5 2 ... Read More