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Bus 304 Statistical Research Analysis. GROUP MEMBERS. Cody Britton Gregory Ortiz Stephano Bonham Carlos Fierro . Sprinter Overview
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Bus 304 Statistical Research Analysis
GROUP MEMBERS Cody Britton Gregory Ortiz Stephano Bonham Carlos Fierro
Sprinter Overview The Sprinter (for all those unfamiliar) is the new Transit Rail System that runs parallel with Highway 78, spanning Oceanside to Escondido. The Rail offers both college students and San Diego County citizens public transportation at low cost. With rising gas prices and congested highways, Students are more inclined to commute by Sprinter. The price for one day fair is nearly $5. The Sprinter is operated by the North County Transit District of Oceanside, the area's public transit agency. The Sprinter is the first passenger train service of any kind along the Escondido Branch since the Santa Fe Railroad discontinued passenger service in 1946. The Vista and Escondido stations are the only extant stations from that era of service. The construction cost amounted to $477 million, significantly more than an early estimate of $60 million, made in 1993
Administered Sample of 100. • Each Research administered 25 survey questionnaires to 25 random • students at CSUSM. • This prevented any potential bias. • 1. Some researchers might feel differently based on Age, Gender, Ethnicity, etc. therefore less likely to administer the survey to those demographics. • 2. Also allowed Sample to be generated from different locations. • Data was compiled in Excel Spreadsheet to compute analysis
Population and generated sample demographics :Cal State San Marcos Total Population: 8,734 Population Age: 49.12% 22 or younger 21.83% 23-25 19.84% 26-35 9.2% 36 or older Sample Age: 55% 22 or younger 31% 23-25 11% 26-35 1% 36 or older
Population and generated sample demographics :Cal State San Marcos Population Gender 37.27% Male 62.72% Female Sample Gender 40% Male 60% Female
Population and generated sample demographics :Cal State San Marcos Population Ethnicity: 3.3% African American 11.2% Asian/ Pacific Islander 21.1% Latino 1% Native American 49.55% Caucasian 6.1% Other Sample Ethnicity: 4% African American 11% Asian/Pacific Islander 22% Latino 0% Native American 57% Caucasian 5% Other 1% No Response
Sample Mean and Variance These Values were generated based on our Sample Survey Questions. Salient questions in our Hypothesis include: Annual Income and Price increase on parking to Influence Decision to ride Sprinter.
Test Hypothesis: “Those who produce a lower annual income are more inclined to ride the Sprinter if price of Parking Rises”. Independent Variable : Annual Income Dependent Variable: Dollar amount increase on Parking Prices that influence individual's choice to ride sprinter Predictions: Our research team predicts that there will be a positive linear correlation between annual income and increase in parking prices to influence decision to commute by Sprinter.
Graph Using the Graph, one can see… A person who has a higher income is less likely to ride the Sprinter if Parking Price at CSUSM rises. They are more likely to pay the new price than to ride the sprinter A person who has lower income is more likely to ride the Sprinter if Parking Prices at CSUSM rises. They are more likely to feel the financial strain of higher parking prices and therefore will look for alternative solutions. Correlation Coefficient .803 This is a high positive correlation coefficient signifying a positive Linear Correlation among the independent and dependent variables.
Regression Analysis Multiple R-.803 (Variables X and Y have a Positive High Linear correlation Equation of the Regression line X Variable: 108.0137 Intercept:11821.585 Line Equation: Degree of Freedom:98 (n-2=100-2) R2=.645 This value is found by taking SSR/SST. Means that 64.5 percent of variation In annual income data for this sample can be explained by the linear relationship between annual income and price increase in parking to influence decision to take Sprinter Standard error: 7576 – This is the measure of the standard deviation of the potential sampling error
Regression Analysis SSR- Sum of Squares Regression 10222402220 Values explained by the regression line SST- sum of Squares Total 15847303600 –Total sum of SSE and SSR P-Value or Significance F 9.03e-24 This value allows us the opportunity to evaluate the extent to which the data disagree with the null hypothesis, not just whether they disagree.
Hypothesis Testing (Correlation, Significance of Regression Slope) Hypothesis: Reject Region Reject Region D.F= n-2= (100-2)=98 -t 0.025=-1.9840 Decision Rule t0.025=1.9840 If t>t/2=1.9840, reject If t< - t/2= -1.9840, Reject Otherwise, do not Reject Because 13.34>1.9840, Reject
Hypothesis Test: Significance Test of Regression Slope Reject Region Reject Region D.F= n-2= (100-2)=98 -t 0.025=-1.9840 t 0.025=1.9840 Because 13.35>1.9840, we should reject the null hypothesis and conclude the true slope is not zero.
Estimation of the Mean with 90% and 95% confidence: Estimation of Population Mean (Annual Income) With 95% confidence With 90% confidence Estimation of Population Mean (Dollar Value Price of Parking must increase to influence decision to take Sprinter) With 95% confidence With 90% confidence
Conclusion: One might ask their self, ”How might this be useful?”. The truth is that our research hypothesis has a great deal of significance. Some individuals who might find our research useful is the Parking and Transit center at Cal State San Marcos. By reviewing our data, they would be able to tell the average maximum amount most CSUSM student would pay for their parking pass before using other transportation services. They may also use our annual revenue average to base their fiancés around. Most importantly, the parking and transit offices at CSUSM would be able to maximize their revenues by charging the largest amount possible before actually losing customers. This would help create price stability. This may also prove beneficial to the new parking structure that is set to be built at CSUSM within the next few year. Conducting a Sample analysis of the school helps researches attain an idea of what people can afford and what they want to afford in our case.
Thank You The End