Quantitative Analysis Of Audio Interface On Footwear User Study

Description of the Empirical Analysis

This report deals on the empirical analysis of the quantitative data on footwear user study. A survey was conducted based on the responses on the audio interface of footwear of 22 participants. The study aims to represent a quantitative analysis of this audio interface and ultimately concludes on the change of the user behaviour due to the change in the audio interface [1].

1. Data Issues

The responses of 22 individuals on 21 variables were recorded along with their changes for high, low, and control frequencies and were represented in the columns. Some variables were recorded for two trials (repetition 1 and repetition 2). There were some missing values too [2].

1. Respondents to problem 1. – Data Cleaning – Treatment for missing values

Usually, when there is missing value in a dataset then, the data field is removed from the dataset. However, the current dataset is small and the data is missing for 30 data fields. Thus, the missing data field(s) in a column is(are) replaced with the average of that particular column instead of removing the field from the dataset [3]. The missing values, which are replaced by mean of all the values of the respective columns.t.

The descriptive statistics of 22 respondents for five different variables are shown below. The chosen five variables with their descriptive statistics are shown below

1. ShoeSizeUK

1. Log score of Body visualization for high frequency

Here, the mean is calculated of the information for repetition 1 and repetition 2 and then the descriptive statistics are obtained using the Data Analysis Tool Pak in Excel.

iii. Z-score of Heel pressure for high frequency

The value of High frequency is the average of high frequency value of repetition 1 and 2.

1. Z-score for foot acceleration at low frequency

1. The GSR Z-score at high frequency

1. Response to problem 3. – Calculation of Confidence interval of Z-score of Galvanic skin response (GSR)

The following table shows the lower bounds and upper bounds of the 95% confidence intervals of Z-score of GSR at High, Low, and Control frequency [7].

To show the comparison of the Z-score of GSR, the averages of each of GSR_Zscore for High, Low, and Control are plotted in a bar chart and the corresponding error bars are added to show the changes due to margins of errors.

From the above bar chart, it is seen that the change in the audio interface is mostly affected by the high frequency, rather than low frequency and control. The Z-scores due to high frequency are above 0.17 with a confidence level of 0.111, which implies that there is 88% chance for the Z-scores with high frequency to fall within that confidence interval.        

1. Response to problem 4. – Calculation of Confidence interval for the proportion of positive valence

The number of positive valence is calculated in Excel using the COUNTIF function and then the proportion is calculated by dividing the positive valence by 22. The confidence interval of one-sample proportion can be calculated by the formula,

Descriptive Statistics of Five Chosen Variables

Where, p? = sample proportion, z = confidence coefficient which is equal to 1.96 for 95% confidence interval. The table below shows the lower bounds and upper bounds of the proportion of positive valence for High, Low, and Control frequency.

The bar chart is shown below to show the comparison among the confidence intervals of the proportion of the positive valence for high, low, and control frequencies. The average of the proportion for the two repetitions has been taken for better result

The above bar chart shows that the high frequency bar has the highest proportion of positive valence with the confidence level 0.38 and there is 61% confidence that the future samples of proportion of positive valence will fall within that confidence interval. The proportion gradually decreases from high frequency to control.

1. Research Questions and Answer
2. Research Question 1:  Does toe pressure change with different audio frequencies?

A one-way ANOVA is constructed where the treatment is Toe-pressure and the variation of audio interface can be present due to variation in the frequency level. The repetition 1 and repetition 2 are averaged for each frequency.

The null hypothesis for the ANOVA is any difference between the three frequencies is due to chance which means the mean values are equal for all. From the ANOVA table above, it can be seen that at 5% level of significance, the p-value = 0.018 (< α =0.05). Therefore, the null hypothesis is rejected and there is at least one difference in the mean values and the audio interface is influenced by the change in the frequency [8].

1. Research Question 2: Does foot acceleration change with different audio frequencies?

A one-way ANOVA is constructed where the treatment is Foot-acceleration and the null hypothesis is the same as above. The repetition 1 and repetition 2 are averaged for each frequency.

The p-value = 0.002491 < the level of significance = 0.05 which leads the null hypothesis to be rejected. Therefore, the variation is present due to change in the frequency level.

1. Research Question 3: Does Arousal change with different audio frequencies?

Here a one-way ANOVA is plotted where the treatment is Arousal and the classes of Arousal variable are based on high frequency, low frequency, and control. The data for each frequency has been recorded for two trials. Thus, an average value of the data of repetition 1 and the data of repetition 2 is taken. After that, the One- way ANOVA is carried out to check the difference in the means for the change in the audio frequencies. Here, the null hypothesis is that there is no difference in the means among the classes of the treatment variable [6]. The ANOVA table is shown below.

At 95% confidence level, α=level of significance = 0.05 < the p-value = 0.38. Thus, the null hypothesis is accepted and it can be concluded that there no change in the mean value of the arousal variable due to frequency and any change is only due to chance.

Conclusion

The above report highlights the change in the audio interface is whether due to chance or only due to frequency. Besides, it also elaborately describes the descriptive statistics of five randomly chosen variables. This quantitative analysis is useful to decide which variables are affecting how much for the footwear interface and how it affects the behavioural changes of the footwear users.

References

[1] J. Lewis, “Usability: Lessons Learned … and Yet to Be Learned”, International Journal of Human-Computer Interaction, vol. 30, no. 9, pp. 663-684, 2014.

[2] G. Cumming, Understanding the new statistics. New York: Routledge, 2012.

[3] A. Hayes and K. Preacher, “Statistical mediation analysis with a multicategorical independent variable”, 2014. [Online]. Available: https://pdfs.semanticscholar.org/dd3f/1055005bda517a081c4949ad9a348b7127b3.pdf. [Accessed: 18- May- 2018].

[4] M. Triola, Elementary Statistics Using Excel. Pearson, 2013.

[5] D. Treiman, “Quantitative Data Analysis”, Google Books, 2018. [Online]. Available: https://books.google.co.in/books?hl=en&lr=&id=c-fOAgAAQBAJ&oi=fnd&pg=PR5&dq=quantitative+analysis+in+statistics&ots=gR2k6yr_LG&sig=RrlmJvyaBJOFA1MZWAney7EIIuM&redir_esc=y#v=onepage&q=quantitative%20analysis%20in%20statistics&f=false. [Accessed: 18- May- 2018].

[6] “Quantitative Data Analysis”, Google Books, 2018. [Online]. Available: https://books.google.co.in/books?hl=en&lr=&id=cfOAgAAQBAJ&oi=fnd&pg=PR5&dq=quantitative+analysis+in+statistics&ots=gR2k6yr_LG&sig=RrlmJvyaBJOFA1MZWAney7EIIuM&redir_esc=y#v=onepage&q=quantitative%20analysis%20in%20statistics&f=false. [Accessed: 18- May- 2018].

[7] J. Muller, W. Pet, E. Pet-Reatsch, R. Servaas, F. Ansems, D. Schwander, G. Firer, H. Lothaller and P. Endler, “Repeatability of Measurements of Galvanic Skin Response – A Pilot Study”, Ww.inter-uni.net, 2013. [Online]. Available: https://ww.inter-uni.net/static/download/publication/komplementaer/p_Muller_et_al_+OCMJ_2013+_Repeatability_Galvanic_Skin_Response.pdf. [Accessed: 18- May- 2018].

[8] J. Hox, M. Moerbeek and R. Van de Schoot, Multilevel Analysis.  

Order an Essay Now & Get These Features For Free:

Turnitin Report

Formatting

Title Page

Citation

Outline

Place an Order