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Investing in a good business is a useful move in managing the issue of financial freedom and development of the economy. Before making the decision to invest, it is advisable to understand more about the area of interest, which improves the chances of making the right decision. For example, it is good to understand the specific business which has high returns and those that high and low risks. In most cases, investment opportunities with high risks have better returns compared to the others. However, the business people are afraid of investing in high-risk investments because of the high chances of making profits. For the few who decide to invest in such business, they end up earning more profits, hence dominating the markets. An example of the high-risk investments includes stock market bonds.
In this paper, business statistics skills will be used to perform some analysis concerning XYZ Company; using compiled dataset that has both continuous and categorical variables. Moreover, an academic review that is related to business investment. In addition, the XYZ workers will be advised regarding the company’s state of business investment. An investor has to understand more about the company to invest and the available investment options. This understanding will help to engage in a good business that will have significant returns for the equivalently invested amounts. There some factors that affect the business investment or define the current situation investing environment. For instance, women might be better investors in terms of the investment decisions and the corresponding returns compared to the men. The following are the other sections of the report; including an academic review, statistical analysis, and conclusion.
Peter Swan wrote an article in March 2017 regarding the differences between male and female on stock markets. The main highlighted difference is that the females spend more time in evaluating the stock before making the investment decision. Therefore, because of the keen observations of the stock trends, female have are perceived to be having a greater chance of being successful. According to Peter, previous research has shown that males were more onto stock markets than the females. However, it has not been supported by providing more information on why that has been happening. Peter swan worked with Joakim and Wei Liu and used Finland stock market data because it was balanced in terms of gender distribution. The data covered a period of 17 years; from 1995 to 2011, which included 1 million investors (Swan, 2017).
It was observed the female investors traded more in 1998 and sold the stock from Nokia compared to men. During this time, Nokia increased the stock prices by 5,000 percent because of the US dollar pressure on the market, hence being a good time to make sales. This kind of a scenario was also observed in 2007 – 2008, when Nokia stock prices boomed and the female investors in Finland was seen to outdo the men. Using this two scenarios, we can presume that the females are better investors in the stock market that the males because they are clever to wait when the stock prices are high to make sales. Females’ rate of investment return rate was 43% on Nokia stock and an overall of 21.4%. The females are said to focus on purchasing stock when the prices fall severally and sell only when they rise substantially. Therefore, it can be assumed that they are more informed compared to the males about the price falls and increases (Swan, 2017).
In this section, bivariate analysis between gender and the return per 1,000 dollars invested will be conducted. The aim is to check their relationships and the definite difference between males and females in investment. Below is the summary table between the two variables.
Average of return in $ per thousand
Count of gender
Variance of return in $ per thousand
According to the table above, 56% of the investors were males and the rest 44% were females. Therefore, we can state that more males than females have invested in XYZ Company. However, the average returns for every $1,000 invested are higher for females compared to the men. It has also been observed that the males’ data has higher variance, which is a clear indication that the females are keener in making investment decisions.
There seems to be a significant difference between males and females on the average of returns in $ per thousand dollars invested in XYZ Company.
We will test if the average returns per $1,000 are greater on females compared to the males. Therefore, the hypothesis will be as shown;
H0: µFemales = µMales
HA: µFemales > µMales
z-Test: Two Sample for Means
Hypothesized Mean Difference
z Critical one-tail
z Critical two-tail
The p-value of a one-sided distribution test is 0.4605, which is greater than the significance level 0.05. Therefore, the null hypothesis is not rejected and it is concluded that there is no difference between the average returns per $1,000 dollars of female and male investors. These results are in contrast to the discussion in section two; where it stated that females purchase stock when at the lowest price and sell at the highest price hence having a higher chance of making more profits. However, from a sample of 100 investors, it has been observed that more males invested and that can be an indication of females being more observant before investing.
95% Confidence Interval
H0: the average returns per $1,000 ≠ $30
H1: The average returns per $1,000 > $30
The table above shows the excel output for 95% confidence interval of returns per $1,000 and a hypothesis test for the claim that the mean of the returns is above $30 for every thousand dollars invested. The obtained 95% confidence interval is $34.73 to $39.97. This indicates the average returns to an investor who invest $1,000 will always be included in the interval provided that the data used is in the same setting with 95% confidence. This is significant returns for the investments.
The hypothetical statement that the average returns are greater than $30 for every thousand invested was tested. The corresponding p-value was very small indicating a highly significant test. Therefore, we can conclude that it is definite that the returns for every $1,000 dollar invested in XYZ Company will be more than $30.
The XYZ workers should be the first people to benefit from the good investment environment created by the company. According to the statistical analysis. It has been observed that females’ returns are higher compared to the males. Therefore, females should invest much more because they have high chances of receiving more returns. Regardless of the higher levels of returns for the females, the percentage of investing was high on males; which indicates that the females are not aware of the chances. Hypothesis test results indicated that it is certain that investing $1,000 is guaranteed to return more than $30 at 95% confidence level. In addition, the 95% confidence interval for the returns per $1,000 was found to be [34.73, 39.97]. This indicates that the investors will earn returns which are between $34.73 and $39.97 with 95% confidence. XYZ has created a good investment platform for its workers and the other interested persons. Moreover, there are low chances of making losses from the investment based on the analyzed data. I would advise the workers to invest as much as they can because it is definite that they will earn significant returns.
In conclusion, business statistics can be used to evaluate potential investment opportunities to provide good advice based on the analysis. It is very important for investors to learn about the available opportunities with their environment. The average returns for the females are not greater than the males’, which indicates that the environment favors both genders. Regardless of what has been analyzed, more can be covered to understand XYZ company investment. For instance, checking the effect of different countries investing in XYZ Company can be tested to test if there is a superior investor or any statistical difference. Also, much can be investigated on the effect of age by analyzing the different age-groups. For instance, it can be hypothesized that investors below 50 years are better investors compared to those older than 50 years.
Swan, P., 2017. Why women beat men on the stock market. [Online] Available at: https://www.abc.net.au/news/2017-03-08/-why-women-are-better-stock-market-investors-than-men/8336534
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