問卷調查在生活上時常遇見，經常是以問卷調查的型式進行資料的彙總和統計，再擬定未來的發展方向。但問卷調查常會涉及個人隱私的問題，屆時受訪者的回覆就各憑自我揭露的意願高低，造成最終所收集後的資料與真實面的差異。
班佛定律是一種以數字0~9各個數字在不同位數出現機率，進行數據判斷是否有人為操控的法則，因只要符合定律的規範，就可直接檢視，所以近期最常利用其定律在鑑識會計與防止舞弊領域。
本研究以班佛定律檢視行政院主計總處的家庭收支調查，以10年為一跨度，共檢視108、98、88和78年度的收入總計、支出總計、食品總計和菸酒總計，並分二組進行對比，查看收入和支出、食品和菸酒，何者是受訪者較願意自我揭露，並以10年為一間距，檢視在數據上是否有變化的趨勢。在計算樣本中每個數字出現的機率後，使用卡方檢驗、Z 統計量檢驗和 Cramer's V 來評估數據是否符合班佛定律。最後，以迴歸分析擬合數據前三位數各數字出現的機率與數字之間的關係。
研究結果顯示家庭收支調查嚴重偏離班佛定律，無論在收入總計、支出總計、食品總計和菸酒總計四個項目上，並無班佛定律的規則可言。另外以每10年為一個跨度，共40年的結果進行比對，其結果也是一樣。利用迴歸分析結果顯示總收入的第一位數數字與其機率呈二次關係。 第二個數字 x 與其機率 y 具有線性關係 y= 0.128-0.06x。 第三個數字與其機率也具有線性關係 y= 0.103-0.001x。本研究顯示，無論以前的人或現在的人，對於隱私的自我揭露或許都是保守的，但也有可能是因社會價值觀的改變所造成，或是樣本不足以代表母體造成家庭收支調查嚴重偏離班佛定律，亦可能因時代的變遷造成班佛定律需再修正，其原因可能是多方面因素所造成的。

Academic research and economic development are usually surveyed in the questionnaire to collect data, statistics and then draw up the direction of future development. However, questionnaire surveys often involve personal privacy questions. Therefore, the respondents replied based on their willingness to disclose themselves. Whether interviewees are willing to disclose themselves is difficult to know from the survey results. This study aims to determine whether the survey results conform to Benford’s law and whether there is a clear trend.

This study uses Benford’s law to examine the data of household income and expenditure survey of the General Accounting Office of the Executive Yuan. The research data include the total income, expenditure, food, tobacco and alcohol collected in 2019, 2009, 1999 and 1989. They are divided into two groups to check "income and expenditure" and " expendi- ture on food, tobacco and alcohol". After calculating the probability of occurrence of each digit in the sample, the Chi-square test, Z-statistic test and Cramer’s V are used to evaluate whether the data population obeys Benford’s law. Finally, perform the regression analysis to fit the relationship between the probability of the first three digits’ occurrence of the data and the digit.

The research results show that the survey data deviates seriously from Benford’s law. The regression analysis shows that the first digit of total income and its probability has a quadratic relationship. The second digit x and its probability y has a linear relationship y= 0.128-0.06x. The third digit and its probability has a linear relationship y= 0.103-0.001x. This result may be that the self-disclosure of privacy is conservative for both former and current people. Still, changes in social values may also cause it or because the sample is not representative of the population. The changes of the times may cause Benford’s law to be revised, which may be caused by various factors.

中文文獻
[1] 王智立、蔡宛容 (2009)，分層隨機作答模式於敏感性問題之一般化研究，管理與系統，第十六卷，第三期，397-414頁。
[2] 吳信宏 (2021)，不同於問卷調查的服務品質衡量方法，品質月刊，57卷5期，37-38頁。
[3] 杜素豪 (2001)，問卷訪問中第三者在場的訪答效應，調查研究，73-102頁。
[4] 余淑吟 (2018)，學習效果與生活滿意度對社群網路使用動機與自我揭露之研究，設計學研究，21卷2期，93-106頁。
[5] 李思壯、黃彥男 (2019)，數位時代之數位隱私保護，國土及公共治理季刊，7卷4期，30-39頁。
[6] 李益興 (2009)，運用班佛法則檢驗台灣公開發行公司盈餘管理之研究，國立台北科技大學／商業自動化與管理研究所。
[7] 林愉玶 (2017)，非誠實作答下兩階段隨機作答設計之貝氏推論，逢甲大學／統計學系統計與精算碩士班。
[8] 林美榕、莊文忠 (2018)，問卷調查題型設計的效應檢證：以「政治知識」測量的隨機實驗為例，選舉研究，25卷1期，37-73頁。
[9] 邱淑芬、鍾吉誠和謝淑玲 (2016)，民眾對於開放資料瞭解及隱私權觀感之研究及分析，電子商務研究，第十四卷，第三期，313-334頁。
[10] 徐敬宏、侯偉鵬 (2020)，「隱私擔憂」的仲介效應：基於對大學生微信使用的結構方程模型分析，傳播與社會學刊，54期，54-94頁。
[11] 陳憶寧、溫嘉禾 (2020)，台灣臉書使用者的隱私行為研究：劍橋分析事件之後，傳播與社會學刊，54期，27-57頁。
[12] 盛杏湲 (2013)，問卷設計，民意調查新論-第三版，157-218頁。
[13] 張棋雅 (2017)，自我揭露於人際親密互動建立歷程之探討，諮商與輔導，381期，26-29頁。
[14] 張陳弘 (2018)，新興科技下的資訊隱私保護：「告知後同意原則」的侷限性與修正方法之提出，臺大法學論叢，47卷1期，201-297頁。
[15] 楊馥綺 (2014)，以自我揭露角度探究Facebook個人隱私劃界，淡江大學/資訊傳播學系碩士班。
[16] 潘明宏、陳志瑋 (譯)，Nachmias, F. C., & Nachmias, D. (著) (2003)，最新社會科學研究方法，韋伯文化出版社，209頁。
[17] 鄭文吉 (2019)，問卷調查要怎麼做、怎麼看，高雄區農業專訊，110期，15-17頁。
[18] 劉育成 (2018)，隱私不再？以身體與訊息作為隱私概念雙重性的社會實作理論觀點探究，資訊社會研究，35期，87-123頁。
[19] 蕭怡靖、游清鑫 (2016)，訪問間隔、訪問情境與受訪者特質影響調查信度之探索研究，民主與治理，第三卷，第二期，83-109頁。
[20] 簡茂發 (1989)，信度與效度，社會及行為科學研究法，323-351頁。

網路文獻
[1] 2019年家庭收支調查，https://win.dgbas.gov.tw/fies/a11.asp?year=108
[2] 行政院主計總處家庭收支調查， https://www.stat.gov.tw/np.asp?ctNode=509&mp=4

英文文獻
[1] Adler, R. B., & Towne, N. (2002). Looking out looking in. Thomson, Singapore.
[2] Altman, I. (1977). Privacy regulation: culturally universal or culturally specific?, Journal of Social Issues, Vol. 33, No. 3, pp. 66-84.
[3] Altman, I., & Taylor, D. (1973). Social penetration: The development of interpersonal relationship. Holt, Rinehart & Winston, Oxford, UK, pp. 79-90.
[4] Bradburn, N. M., & Sudman, S. (1980). Improving interview method and questionnaire design: Response effects to threatening questions in survey research. San Francisco, CA: Jossey-Bass.
[5] Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Beverly Hills, CA: Sage.
[6] Carslaw, C. (1988). Anomalies in income numbers: Evidence of goal-oriented behavior, Accounting Review, pp. 321-327.
[7] Christofides, T. C. (2003). A Generalized Randomized Response Technique, Metrika, Vol. 57, No. 2, pp. 195-200.
[8] Clarke, R. (1999). Internet Privacy Concerns Confirm the Case for Intervention. Communications of the ACM, No. 42, pp. 60-67.
[9] DeVellis, R. F. (1991). Scale development: Theory and applications. Newbruy Park, CA: Sage, pp. 67-69.
[10] DeVito, J. A. (2003). Human Communication: The basic course (9th ed.). Allyn & Bacon. Boston U.S.
[11] Derlega, V. J., Margulis, S. T., Metts S., & Petronio, S. (1993). Self-Disclosure. Newrbury Park, CA: Sage.
[12] Derlega, V., Winstead, B., Wong, P., & Greenspan, M. (1987). Human Communication: The basic course (9th ed.). Allyn & Bacon, Boston U.S.
[13] Drake, P. D., and Nigrini, M. J. (2000). Computer assisted analytical procedures using Benford’s law, Journal of Accounting Education, No. 18, pp. 127-146.
[14] Greenberg, B. G., Abul-Ela, A. A., Simmons, W. R., and Horvitz, D. G., (1969). The Unrelated Question Randomized Response Model：Theoretical Framework, Journal of the American Statistical Association, Vol. 64, No. 326, pp. 520-539.
[15] Hill, T. P. (1995). A Statistical Derivation of the Significant-digit Las, Statistical Science, 10 (4), pp. 354-363.
[16] Huang, K. C. (2004). A Survey Technique for Estimating the Proportion and Sen-sitivity in a Dichotomous Finite Population, Statistica Neerlandica, 58, pp. 75-82.
[17] Johnson (2005). Fraud Detection with Benford ’s Law, Accountancy Ireland, No. 37, pp. 16.
[18] Jourard, S. M. (1971). Self-disclosure: An experimental analysis of the transparent self. Wiley Interscience, NY.
[19] Kelly, J. R., & McGrath, J. E. (1988). On time and method. Newbury Park, CA:Sage.
[20] Lyman, H. B. (1986). Test scores and what they mean (4th ed.). Englewood Cliffs, NJ: Prentice-Hall, pp. 32-37.
[21] Nigrini, M. J., and Mittermaier, L. J. (1997). The use of Benford’s law as an aid in analytical procedures, Auditing, No. 16, pp. 52-67.
[22] Nigrini, M. J. (1996). A Taxpayer Compliance Application of Benford's Law, Journal of the Ame1ican Taxation Association, No. 18, pp. 72-91.
[23] Nigrini, M. J. (1992). The detection of income tax evasion through an analysis of digital frequencies, Dissertation, University of Cincinnati, Cincinnati.
[24] Nigrini, M. J., and Miller, S. J. (2009). Data Diagnostics Using Second-Order Tests of Benford’s law, Auditing-a Journal of Practice & Theory, 28 (2), pp. 305-324.
[25] Nigrini, M. J. (2011). Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations, Wiley.
[26] Nowak, G. J. & Phelps, J. (1995). Direct marketing and the use of individual-level consumer information, determining how and when “privacy” matters. Journal of Direct Marketing, No. 9, pp. 46-60.
[27] Porst, R., & Zeifang, K. (1987). A description of the German general social survey test-retest study and a report on the stability of the sociodemographic variables. Sociological Methods and Research, No. 15, pp. 177-218.
[28] Quick, R., and Wolz, M. (2005). Benford’s law in German financial statements, Institute for Business Studies, Publications of Darmstadt Technical University.
[29] Skousen, C. J., Guan, L. & Wetzel, T. S. (2004). Anomalies and Unusual Patterns in Reported Earnings: Japanese Managers Round Earnings, Journal of International Financial Managejment and Accounting, 15 (3), pp. 212-234.
[30] Thomas, J. K. (1989). Unusual patterns in reported earnings, Accounting Review, pp 773-787.
[31] Tracol, X. (2014). Legislative genesis and judicial death of a directive: The European Court of Justice invalidated the data retention directive thereby creating a sustained period of legal uncertainty about the validity of national laws which enacted it. Computer Law & Security Review, 30 (6), pp. 736-746.
[32] Van der Sloot, B. (2015). Do privacy and data protection rules apply to legal persons and should they? A proposal for a two-tiered system. Computer Law & Security Review, No. 31, pp. 26-45.
[33] Warner, S. L. (1965). Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias, Journal of the American Statistical Association, No. 60, pp. 63-69.
[34] Westin, AF. (1967). Privacy and freedom. Atheneum Publishers, New York.
[35] Yang, J. J., Li, J. Q., & Niu, Y (2015). A hybrid solution for privacy preserving medical data sharing in the cloud environment. Future Generation Computer Systems, pp.74-86.