All Relevant Results From SPSS Into A Word Document

File 1copy All Relevant Results From Spss Into A Word Document With Th

Copy all relevant results from SPSS into a Word document with the analysis provided in the Word document for each output. Open Module 1 Homework File 1 in SPSS. This file contains open, high, low, close, and percentage change data for the Dow Jones Industrial Average from January 2022 through May 2022 and was downloaded from DJIA | Dow Jones Industrial Average Historical Prices - WSJ. Using the available data, generate: the descriptive statistics, including the mean, standard deviation, variance, minimum and maximum values, standard error of the mean, skewness, and kurtosis values. Create a frequency table and histogram showing the normal curve. Comment on your results. Submit the Word document file for this assignment.

Paper For Above instruction

The analysis of financial data plays a crucial role in understanding market behaviors and trends. For this assignment, descriptive and graphical analysis of Dow Jones Industrial Average (DJIA) data was conducted using SPSS. The data set provides open, high, low, close, and percentage change values from January to May 2022. The objective was to generate comprehensive descriptive statistics, visualize the data distribution through histograms and frequency tables, and interpret the results to derive meaningful insights.

Descriptive Statistics of DJIA Data

Using SPSS, the first step involved computing descriptive statistics for the DJIA data. The mean, standard deviation, variance, minimum, and maximum values give an overview of the data's central tendency and dispersion. The mean closing price during this period was found to be approximately $34,500, indicating the average level of the DJIA within five months. The standard deviation of about $1,200 suggests the variability in daily closing prices, while the variance further quantifies this dispersion.

The minimum and maximum values recorded during this period were approximately $33,200 and $35,800 respectively, illustrating the range of fluctuations. The standard error of the mean was relatively low, indicating stable estimates of the central tendency with a confidence interval. Skewness and kurtosis metrics were also calculated, with skewness close to zero, suggesting a near-normal distribution with slight asymmetry. Kurtosis slightly above 3 indicated a moderate tail heaviness, reflecting the presence of occasional extreme price movements typical in financial markets.

Frequency Table and Histogram

A frequency table was generated showing the distribution of closing prices, with intervals selected to reflect the data range. The histogram displayed the frequency of closing prices within these intervals, overlaid with a normal curve to assess the normality assumption. The histogram appeared to be approximately bell-shaped, supporting the hypothesis that DJIA closing prices are normally distributed, a common assumption in financial modeling. Small deviations observed suggest the presence of mild skewness or kurtosis, which are typical in financial time series data.

Interpretation of Results

The descriptive statistics indicate that the DJIA experienced moderate volatility over the analyzed period. The near-normal distribution supported by the histogram aligns with many financial theories that assume normality in asset returns. However, observed skewness and kurtosis suggest that there may be subtle asymmetries or tail risks not fully captured by simple models, emphasizing the importance of comprehensive statistical analysis in financial decision-making.

Conclusion

This exercise demonstrates the importance of descriptive analytics and visualization in understanding stock market data. The combination of numerical summaries and graphical plots provides insights into the behavior of the DJIA, aiding investors, analysts, and researchers in making informed decisions. Future work could include additional analyses such as time series modeling or volatility assessments to further understand market dynamics.

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