Answer the following question in once sentence each?

Identify the statistic(s) to be used that will best utilize the data to answer the research question(s) ?

Indicate why the statistics are appropriate and why the chosen statistics do not violate the assumptions of the planned statistical tests (e.g., normality) ?

Identify which data sets would be needed to perform that analysis and how they would be used. You do not need to complete the calculations but do identify how the data you are using would enter into the statistics to be calculated ?

Research question: What motivates financial securities fraud in corporate finance, and how effective are regulatory and market mechanisms in deterring or detecting it?

Research below:

Purpose: The study aims to review recent research in corporate finance on financial securities frauds. It focuses on three main areas: factors that motivate fraudulent criminal activities, regulatory and market-based mechanisms that deter or detect fraud, and the economic and social consequences of financial fraud (Yu, 2013).

Even though, I do not actively work in the criminal justice field or have a job at the moment I find the research topic important because securities fraud crimes affect economic stability.

The units of analysis in this study are the internal and external factors that motivate fraudulent activities, the regulatory and market-based mechanisms that deter or detect fraud, and the economic and social consequences of financial fraud.

Identifying Weaknesses of securities fraud, we can identify weaknesses in current practices and policies (Yu, 2013). This could be loopholes in regulations, inadequate enforcement, or lack of transparency that allows fraudulent activities to occur.

Developing Preventive Measures, this could involve strengthening regulations, improving enforcement mechanisms, or enhancing transparency and accountability in the securities market.

Improving Education and Awareness among investors. By understanding how fraud occurs, investors can be better equipped to identify and avoid potential scams.

Informing Policy Decisions could reveal that certain types of securities or transactions are particularly prone to fraud; regulators might decide to impose stricter controls on them.

Evaluating Effectiveness of Current Programs aimed at preventing securities fraud. If these programs are not effective, they can be revised or replaced with more effective.

Target population in this study are investors affected by securities fraud crime.

100 investors victims of securities fraud would be the subjects which I can draw a sample, specifically those who have reported securities fraud.

The research will employ a stratified random sampling technique dividing the population into distinct groups based on specific characteristics and selecting samples from each group randomly.

The sample size of investors that is attainable in this study to focus on is of 100 subjects. The resources that will be used to study securities fraud victims are interviews, surveys, academic journals and government resources, preferably biased free.

Securities fraud, a deceptive practice in the stock or commodities markets that induces investors to make purchase or sale decisions based on nefarious information. There are implications for more than just individual investors, affecting the integrity of financial markets, the stability of financial institutions, and the overall health of economies. Thousands of securities fraud cases are filed every year, indicating the problem's widespread nature (Dyck, Morse & Zingales, 2010). This is concerning because it brings to light that more individuals are engaging in fraudulent criminal activity for their benefit even though it affects the people or organizations they defraud. Securities fraud can have significant economic impacts on individuals, businesses, and even the economy as a whole (Cumming, Johan & Li, 2011). Securities fraud can lead to substantial financial losses for individual investors who, relying on false information, may invest in stocks or other securities that are not as valuable as they believe. Furthermore, widespread securities fraud is likely to undermine trust in the financial markets, resulting in reduced investment, slower economic growth, and perhaps even a recession.

Sampling technique and data collection strategy

Mixed-methods approach combines quantitative and qualitative data to study securities fraud's impact on investors. (Brancale & Blomberg, 2019). The research will employ a stratified random sampling technique. Stratified sampling involves dividing the population into distinct groups based on specific characteristics and selecting samples from each group randomly. In this case, the population could be divided into strata like financial institutions, individual investors, and regulatory bodies.

Hypothesis: There is a significant statistical difference that implementation of stricter regulatory measures reduces the incidence of securities fraud.

Null Hypothesis: There is not a significant statistical difference that implementation of stricter regulatory measures reduces the incidence of securities fraud.

Type I Error

A Type I error is committed when the researcher rejects a true null hypothesis (Banerjee et al., 2009). In the context of securities fraud crime, this would mean concluding that increased regulation does decrease the occurrence of securities fraud when it does not.

Outcomes constituting a Type I error

In this case, stricter regulations cause the observed data to suggest that securities fraud has decreased when, in fact, the reduction is attributed to other factors not associated with the implemented regulations (Picciotto & Haines, 2018).

Decision-makers leading regulatory agencies and policy might consider the new measures efficient in addressing fraud, which can lead them to spend resources and efforts on them while excluding other potentially efficient methods.

Type II Error

Type II error, on the other hand, is committed when the null hypothesis is not rejected when, in fact, it is false (Banerjee et al., 2009). In this case, it would mean not being able to generalize about a situation where stricter regulatory measures decrease the occurrence of securities fraud when, in fact, they do.

Outcomes constituting a Type II error

Better regulatory policies are deployed, but the analysis does not depict a decline in securities fraud, which gives a wrong impression that regulatory measures are not helpful (Picciotto & Haines, 2018).

Decision makers may refrain from applying a more robust regulatory framework in the future; this can sometimes lead to failure to adopt regulatory strategies that could effectively curb securities fraud.

Level of Significance

0.05 (5%):

Statistical Meaning: 5% chance of rejecting the null hypothesis when it is true.

Contextual Meaning: 5% risk of concluding that stricter regulations reduce securities fraud when they do not, balancing leniency and stringency.

0.01 (1%):

Statistical Meaning: 1% chance of rejecting the null hypothesis when it is true.

Contextual Meaning: Very low tolerance for Type I errors, chosen if false conclusions about regulation effectiveness are highly costly.

0.10 (10%):

Statistical Meaning: 10% chance of rejecting the null hypothesis when it is true.

Contextual Meaning: Higher tolerance for Type I errors, prioritizing detection of true regulatory effects despite some false positives.

Type I Error (False Positive):

Research Context: Concluding that stricter regulations reduce securities fraud when they do not.

Consequences: Misallocation of resources.

External factors that motivate fraudulent activities: Economic downturns, competitive pressures, weak regulatory environments.

Regulatory and market-based mechanisms that deter or detect fraud: Laws, regulations by the government. Market based mechanisms to prevent fraud; oversight by investors or auditors.

Economic and social consequences of financial fraud; Market instability. Loss of social trust in financial institutions.

Data sources:

Government and Regulatory Bodies: These sources provide data on laws and regulations related to securities fraud. They include the U.S. Securities and Exchange Commission (SEC), Financial Industry Regulatory Authority (FINRA), and other similar bodies worldwide.

Financial News and Media Reports: These sources provide real-time information on securities fraud cases and their impact on the market and society. They include financial news websites, newspapers, and business magazines.

Surveys and Interviews: These sources provide qualitative data on the motivations behind securities fraud and the effectiveness of regulatory and market-based mechanisms. They can be conducted with industry professionals, convicted fraudsters, and other relevant individuals.

Government Statistics: These sources provide data on the frequency of securities fraud cases and the overall economic conditions. They include databases maintained by the SEC, U.S. Bureau of Economic Analysis, U.S. Bureau of Labor Statistics, etc.

Regulatory Bodies: These sources provide data on the presence and effectiveness of regulations against securities fraud. They include the SEC, FINRA, and other similar bodies worldwide.

Market Research Firms: These sources provide data on the perceived trustworthiness of financial markets. They include firms like Nielsen, Ipsos, and others that conduct market surveys and studies.

Dependent variables

Frequency of Securities Fraud Cases (Omidi & Min, 2017).

Level of Measurement: Interval or Ratio (count data).

Financial Market Integrity:

Level of Measurement: Ordinal (ratings or rankings).

Independent variables

Economic Conditions: Level of Measurement: Interval or Ratio (economic indicators such as GDP, unemployment rate).

Regulatory Measures: Level of Measurement: Nominal (presence or absence of specific regulations.

Public Awareness Campaigns: Level of Measurement: Ordinal (ratings of awareness levels).

Dependent and Independent variables identified:

Dependent Variables:

Frequency of Securities Fraud Cases: Number of securities fraud cases filed annually.

Financial Market Integrity: Perceived trustworthiness of financial markets, influenced by securities fraud incidents.

Independent Variables:

Economic Conditions: Overall economic health, indicated by metrics like GDP and unemployment rate (Omidi & Min, 2017).

Regulatory Measures: Presence and effectiveness of regulations against securities fraud.

Public Awareness Campaigns: Level of public awareness about securities fraud and its consequences, measured by ordinal ratings or rankings.

Key relationships among variables and the hypothesis's:

The relationship between internal factors (e.g., personal financial gain, pressure to meet financial targets) and the occurrence of securities fraud.

The relationship between external factors (e.g., economic downturns, competitive pressures, weak regulatory environments) and the effectiveness of regulatory and market-based mechanisms in deterring or detecting securities fraud (Yu,2013).

Hypothesis: There is a significant statistical difference that implementation of stricter regulatory measures reduces the incidence of securities fraud.

H2: There is not a significant statistical difference that implementation of stricter regulatory measures reduces the incidence of securities fraud.