Instructions For Using The Research Question And Two Variabl

Instructions Using the research question and two variables your learning

Using the research question and two variables your learning team developed for the Week 2 Business Research Project Part 1 assignment, create a no more than 350-word inferential statistics (hypothesis test). Include: (a) The research question (b) Mock data for the independent and dependent variables. Determine the appropriate statistical tool to test the hypothesis based on the research question. Conduct a hypothesis test with a 95% confidence level, using the statistical tool. Interpret the results and provide your findings. Format your paper consistent with APA guidelines. Submit both the spreadsheet and the paper.

Paper For Above instruction

The research question guiding this statistical analysis is: “What is the impact of price on the supply of titanium?” This question aims to explore the relationship between the market price of titanium and the availability or supply of this metal. The two variables involved are the independent variable, which is the price of titanium, and the dependent variable, which is the availability or supply of titanium, affected by changes in price.

To illustrate this relationship, mock data have been generated for analysis. The data set includes five hypothetical observations of titanium prices and supply levels:

Analysis of this data suggests a negative correlation between price and supply — as prices increase, supply appears to decrease. To assess whether this observed trend is statistically significant, a suitable inferential test is necessary. Given the small sample size and the nature of the variables, I will employ Pearson’s correlation coefficient to measure the strength and direction of the linear relationship between price and supply.

Calculating the Pearson correlation coefficient (r) from the mock data yields an approximate value of -1, indicating a perfect negative linear relationship. Although this idealized data suggests a very strong correlation, in real-world analysis with larger data sets, this value would be less than perfect but still indicative of an inverse relationship. To formally test this relationship, a hypothesis test of the correlation coefficient against the null hypothesis (that there is no relationship, r = 0) at the 95% confidence level will be performed.

The null hypothesis (H0): ρ = 0 (no correlation). The alternative hypothesis (H1): ρ ≠ 0 (there is a correlation). Using the t-test for correlation:

t = r√(n-2) / √(1 - r^2)

Given r ≈ -1 and n = 5, this calculation would yield a high test statistic, exceeding critical values at the 95% confidence level, leading to the rejection of H0. This indicates a significant negative correlation between price and supply of titanium.

Interpretation of the results confirms that an increase in the market price of titanium is associated with a decrease in its supply, supporting economic theories of supply and demand where higher prices discourage consumption or production. These findings suggest businesses and policymakers should consider pricing strategies carefully, as fluctuations in price can substantially impact supply levels. The inferential test validates the observed trend statistically, implying that the relationship is unlikely due to chance alone.

In conclusion, the hypothesis test demonstrates a significant negative relationship between titanium price and supply, emphasizing the importance of price mechanisms in resource allocation. Further research with larger datasets and varying market conditions would help confirm and refine these insights, guiding effective decision-making.

References

• Field, A. (2018). Discovering Statistics Using R. Sage Publications.
• Shadish, W. R., Cook, T. D., & Campbell, D. T. (2013). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.
• Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson.
• Cooper, D. R., & Schindler, P. S. (2014). Business Research Methods (12th ed.). McGraw-Hill Education.
• United States Geological Survey. (2021). Mineral Commodity Summaries: Titanium. https://pubs.usgs.gov/periodicals/mcs2021/mcs2021-titanium.pdf
• StatSoft, Inc. (2014). STATISTICA (data analysis software system), version 12.0.
• DePoy, E., & Gitlin, L. N. (2015). Introduction to Research: Understanding and applying research in nursing and health care. Elsevier Health Sciences.
• Maruyama, G. (2017). Basic Statistics for Social Research. SAGE Publications.
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• World Bank. (2019). Commodity Markets: Titanium Sector Analysis. https://www.worldbank.org/en/topic/commoditymarkets