Some people overestimate the benefits of certain kinds of foods, such as organic foods, while others underestimate it. Previous studies have found that reducing people’s self-assessed knowledge successfully moderated these extreme attitudes. In this study, we investigated interventions to reduce people’s self-assessed knowledge and to moderate attitude extremity. We examined extreme attitudes toward organic foods and investigated the effects of implementing two intervention methods to moderate their attitude: (1) providing knowledge on organic food after asking them some questions and (2) simply providing them with knowledge. We conducted a two-factor mixed-design experiment with 653 college-educated Japanese women. In the first condition, before knowledge provision, participants were asked to answer questions about organic foods and were then informed of the correct answer and whether their answer was correct (Q&A Intervention). This step was based on an intervention conducted in a previous study to reduce their self-assessed factual knowledge. In the second condition, participants were simply provided with knowledge without being asked to answer any questions (Simple Intervention). The results showed that both intervention methods, on average, decreased the participants’ self-assessed knowledge and attitude extremity. Therefore, simply providing knowledge may be effective in reducing their self-assessed factual knowledge and moderating their extreme attitudes toward organic foods.

Context

An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.

The company markets its courses on several websites and search engines like Google. Once these people land on the website, they might browse the courses or fill up a form for the course or watch some videos. When these people fill up a form providing their email address or phone number, they are classified to be a lead. Moreover, the company also gets leads through past referrals. Once these leads are acquired, employees from the sales team start making calls, writing emails, etc. Through this process, some of the leads get converted while most do not. The typical lead conversion rate at X education is around 30%.

Now, although X Education gets a lot of leads, its lead conversion rate is very poor. For example, if, say, they acquire 100 leads in a day, only about 30 of them are converted. To make this process more efficient, the company wishes to identify the most potential leads, also known as ‘Hot Leads’. If they successfully identify this set of leads, the lead conversion rate should go up as the sales team will now be focusing more on communicating with the potential leads rather than making calls to everyone.

There are a lot of leads generated in the initial stage (top) but only a few of them come out as paying customers from the bottom. In the middle stage, you need to nurture the potential leads well (i.e. educating the leads about the product, constantly communicating, etc. ) in order to get a higher lead conversion.

X Education wants to select the most promising leads, i.e. the leads that are most likely to convert into paying customers. The company requires you to build a model wherein you need to assign a lead score to each of the leads such that the customers with higher lead score h have a higher conversion chance and the customers with lower lead score have a lower conversion chance. The CEO, in particular, has given a ballpark of the target lead conversion rate to be around 80%.

Content

Variables Description * Prospect ID - A unique ID with which the customer is identified. * Lead Number - A lead number assigned to each lead procured. * Lead Origin - The origin identifier with which the customer was identified to be a lead. Includes API, Landing Page Submission, etc. * Lead Source - The source of the lead. Includes Google, Organic Search, Olark Chat, etc. * Do Not Email -An indicator variable selected by the customer wherein they select whether of not they want to be emailed about the course or not. * Do Not Call - An indicator variable selected by the customer wherein they select whether of not they want to be called about the course or not. * Converted - The target variable. Indicates whether a lead has been successfully converted or not. * TotalVisits - The total number of visits made by the customer on the website. * Total Time Spent on Website - The total time spent by the customer on the website. * Page Views Per Visit - Average number of pages on the website viewed during the visits. * Last Activity - Last activity performed by the customer. Includes Email Opened, Olark Chat Conversation, etc. * Country - The country of the customer. * Specialization - The industry domain in which the customer worked before. Includes the level 'Select Specialization' which means the customer had not selected this option while filling the form. * How did you hear about X Education - The source from which the customer heard about X Education. * What is your current occupation - Indicates whether the customer is a student, umemployed or employed. * What matters most to you in choosing this course An option selected by the customer - indicating what is their main motto behind doing this course. * Search - Indicating whether the customer had seen the ad in any of the listed items. * Magazine
* Newspaper Article * X Education Forums
* Newspaper * Digital Advertisement * Through Recommendations - Indicates whether the customer came in through recommendations. * Receive More Updates About Our Courses - Indicates whether the customer chose to receive more updates about the courses. * Tags - Tags assigned to customers indicating the current status of the lead. * Lead Quality - Indicates the quality of lead based on the data and intuition the employee who has been assigned to the lead. * Update me on Supply Chain Content - Indicates whether the customer wants updates on the Supply Chain Content. * Get updates on DM Content - Indicates whether the customer wants updates on the DM Content. * Lead Profile - A lead level assigned to each customer based on their profile. * City - The city of the customer. * Asymmetric Activity Index - An index and score assigned to each customer based on their activity and their profile * Asymmetric Profile Index * Asymmetric Activity Score * Asymmetric Profile Score
* I agree to pay the amount through cheque - Indicates whether the customer has agreed to pay the amount through cheque or not. * a free copy of Mastering The Interview - Indicates whether the customer wants a free copy of 'Mastering the Interview' or not. * Last Notable Activity - The last notable activity performed by the student.

Acknowledgements

UpGrad Case Study

Inspiration

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This dataset explores the number of certified organic farms reporting to the 2001 Canadian Census. ... : not applicable. Notes: - The question on certified organic farming was new in 2001. - Due to both undercoverage and response errors, the number of farms producing certified organic products for sale is under-reported. 1. Respondents could choose more than one category. Source: Statistics Canada, Census of Agriculture. Last modified: 2004-05-30.

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.

Abstract copyright UK Data Service and data collection copyright owner. The Workplace Employment Relations Survey (WERS) series is a periodic national survey of people at work. So far, the surveys have been conducted in 1980, 1984, 1990, 1998 and 2004. The purpose of each survey in the WERS series has been to provide large-scale, statistically reliable evidence about a broad range of industrial relations and employment practices across almost every sector of the economy in Great Britain. This evidence is collected with several objectives in mind. The survey aims to provide a mapping of employment relations practices in workplaces across Great Britain, monitor changes in those practices over time, inform policy development and permit an informed assessment of the effects of public policy, and bring about a greater understanding of employment relations as well as the labour market. The series was originally known as the Workplace Industrial Relations Survey, or WIRS - the name was changed in 1998 to better reflect the contemporary content of the series. The WIRS/WERS series from 1980 onwards is held at the UKDA under GN 33176. The Workplace Employee Relations Survey Private Sector Panel, 1998-2004 study analyses WERS workplace panel data to further understanding of the factors associated with the survival and growth of British private sector workplaces in the 1990s. It identified the independent effects of workplace size, age, technology, research and development and human capital investment on survival and growth. It explored these relationships among different types of workplace, notably those in single-establishment and multi-establishment firms. It tested the sensitivity of results to alternative estimation techniques including selection-adjusted estimates of employment growth accounting for the probability of workplace survival. The results were sensitive to sample selection modelling. As such, the study was among the first to demonstrate the importance of tackling sample selection to properly understand the factors affecting workplace employment growth. Important differences are indicated in factors associated with growth and survival in single-site and multi-site firms. The study demonstrates that factors associated with employment growth per se can differ from those that influence internal growth, i.e. organic growth from within the workplace as opposed to growth associated with ownership change. The study extended the literature on workplace employment growth to consider human capital investments and demonstrates that, whereas some workforce composition variables do indeed affect workplace growth and survival, direct measures of human capital investment prolong the life of workplaces, but have no significant impact on workplace employment growth. Syntax code and logs used in the derivation of variables are included in the dataset, but otherwise documentation for this study is limited. Users are strongly encouraged to consult the documentation for the main WERS 2004 study (held under SN 5294) and the WERS 98 panel study (held under SN 4026). Further information about WERS is available from the WERS 2004 Information and Advice Service (WIAS) web site, and the Department for Business, Enterprise and Regulatory Reform (BERR) 2004 Workplace Employee Relations Survey and 1998 Workplace Employee Relations Survey web pages. Main Topics: Topics covered include: establishment size and structure, and changes to them over time; business ownership; organisation history; vacancies; location of organisation and workplaces; training; mergers and takeovers; unions; employee relations; profit-sharing, bonuses and other employee benefits; demographics of workforce (e.g. ethnicity, gender distribution, numbers of part-time and full-time employees); skill levels and occupational status of workforce; temporary workers; workforce reductions; working time arrangements; quality assessment; record-keeping; benchmarking and performance monitoring; technology and working practice changes; pay levels and wage determination. See main WERS 2004 documentation for details.

Monthly average retail prices for selected products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

Soybeans fell to 1,017 USd/Bu on October 3, 2025, down 0.66% from the previous day. Over the past month, Soybeans's price has risen 0.49%, but it is still 2.00% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Soybeans - values, historical data, forecasts and news - updated on October of 2025.

Wheat traded flat at 514.75 USd/Bu on October 3, 2025. Over the past month, Wheat's price has risen 2.49%, but it is still 12.72% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Wheat - values, historical data, forecasts and news - updated on October of 2025.

Non Farm Payrolls in the United States increased by 22 thousand in August of 2025. This dataset provides the latest reported value for - United States Non Farm Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Sugar rose to 16.49 USd/Lbs on October 3, 2025, up 0.43% from the previous day. Over the past month, Sugar's price has risen 5.10%, but it is still 28.34% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Sugar - values, historical data, forecasts and news - updated on October of 2025.

Cotton rose to 65.29 USd/Lbs on October 3, 2025, up 0.31% from the previous day. Over the past month, Cotton's price has risen 1.04%, but it is still 10.60% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cotton - values, historical data, forecasts and news - updated on October of 2025.

Coal fell to 104.85 USD/T on October 2, 2025, down 0.66% from the previous day. Over the past month, Coal's price has fallen 3.36%, and is down 26.47% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coal - values, historical data, forecasts and news - updated on October of 2025.

Japan's main stock market index, the JP225, rose to 45770 points on October 3, 2025, gaining 1.85% from the previous session. Over the past month, the index has climbed 7.49% and is up 18.46% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on October of 2025.

Sunflower Oil rose to 1,359 INR/10 kg on October 1, 2025, up 0.38% from the previous day. Over the past month, Sunflower Oil's price has risen 0.12%, and is up 15.61% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Sunflower Oil.

Inflation Rate in Argentina decreased to 33.60 percent in August from 36.60 percent in July of 2025. This dataset provides the latest reported value for - Argentina Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Urals Oil fell to 59.99 USD/Bbl on October 2, 2025, down 2.04% from the previous day. Over the past month, Urals Oil's price has fallen 1.46%, and is down 16.17% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urals Crude.

Thailand's main stock market index, the SET 50, rose to 836 points on October 3, 2025, gaining 0.49% from the previous session. Over the past month, the index has climbed 2.53%, though it remains 8.84% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Thailand. Thailand Stock Market (SET50) - values, historical data, forecasts and news - updated on October of 2025.

Taiwan's main stock market index, the Taiwan Stock Market Index, rose to 26761 points on October 3, 2025, gaining 1.45% from the previous session. Over the past month, the index has climbed 10.68% and is up 19.99% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Taiwan. Taiwan Stock Market Index (TWSE) - values, historical data, forecasts and news - updated on October of 2025.