During a survey held in early 2021, it was found that 83 percent of adults aged between 18 and 29 years old had read a book in any format in the previous year, up by two percent from the share who said the same in 2019. The survey results showed that adults within this age category were more likely than older respondents to have read a book within the last twelve months.

Book readers in the U.S.

While it is mostly believed that book reading is a vanishing pastime, particularly among Millennials, surveys among consumers in the U.S. have shown the opposite. The share of book readers in the U.S. has varied from 72 percent to 79 percent between 2011 and 2016.

In regards to age of book readers in the country, a 2016 survey shows about 80 percent of respondents between the ages of 18 to 29 had read at least one book in the previous 12 months, the highest share amongst all age groups. About 73 percent of the respondents aged between 30 to 49 years old said they read at least one book in the last 12 months. The share among respondents between 50 and 64 years old stood at 70 percent, whereas 67 percent of respondents aged 65 plus stated reading book during the time measured. In terms of education level, book readers in the U.S. are more likely to have a college degree, or at least some college education – 86 percent and 81 percent respectively. Women in the U.S. read slightly more than men; 68 percent of male respondents started reading at least one book in the previous 12 months, against 77 percent of female respondents that said the same.

Despite the rise of digital platforms and the rising popularity of e-reading devices such as Kindle, Kobo and others, printed books still remain the most popular book format in the U.S., as 65 percent of Americans stated preference for printed books in 2016. E-books were consumed by 28 percent of respondents in 2016, whereas audio books were listened by 14 percent of the respondents. Millennials accounted for the largest share of printed book readers in the U.S. – 72 percent as of 2016.

According to the results of a survey held in the United States, the share of Americans who had read more than ** books in the last three months stood at **** percent in February 2024. However, **** percent had not any read any books in the three months running up to the survey.

A survey examining book readership in the United States as of February 2021 showed that ** percent of 18-to-29-year-olds had read a print book in the last year. The share was slightly lower among older adults, though more than ** percent of respondents in each age group reported having read at least one printed book in the 12 months leading to the survey.

The Progress in International Reading Literacy Study, 2011 (PIRLS 2011), is part of the Progress in International Reading Literacy Study (PIRLS) program. PIRLS 2011 (https://nces.ed.gov/surveys/pirls/) is a cross-sectional study that provides international comparative information of the reading literacy of fourth-grade students and examines factors that may be associated with the acquisition of reading literacy in young students. The study was conducted using questionnaires and direct assessments of fourth-grade students. In the United States a total of 370 schools and 12,726 fourth-grade students participated in 2011. The final weighted student response rate was 96 percent and the final weighted school response rate was 85 percent. The overall weighted response rate was 81 percent. Key statistics produced from PIRLS 2011 are how well fourth-grade students read, how students in one country compare with students in another country, how much fourth-grade students value and enjoy reading, and internationally, how the reading habits and attitudes of students vary.

Recent data revealed that ** percent of Boomers who responded to a survey held in the United States in March 2020 were more likely to read books as a result of the coronavirus outbreak, compared to ** percent of Gen X respondents.Millennials were the most likely to read more books to keep themselves entertained whilst self-isolating, with ** percent saying that they were more inclined to read books, ***** percent higher than all adults in total.

A survey held in 2021 found that ** percent of non-Hispanic Black respondents had read at least one book in the previous 12 months, up from ** percent who said the same during the 2019 study. Non-Hispanic White adults were the most likely group to have read a print or digital book in the last year.

The Screen Reader market has witnessed significant growth over the years, emerging as a crucial component in enhancing accessibility in digital environments. As assistive technology, screen readers play a vital role in enabling visually impaired users to navigate computers and mobile devices by converting text into

This table contains 336 series, with data for years 1997 - 2009 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...); Household spending, reading materials (6 items: Total reading materials and other printed matter; Newspapers; Magazines and periodicals; Books and pamphlets (excluding school books); ...); Statistics (4 items: Average expenditure; Percent of households reporting; Estimated number of households reporting; Median expenditure per household reporting).

About this dataset

Context

The dataset tabulates the population of Reading town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Reading town. The dataset can be utilized to understand the population distribution of Reading town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Reading town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Reading town.

Key observations

Largest age group (population): Male # 70-74 years (46) | Female # 55-59 years (54). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Reading town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Reading town is shown in the following column.
• Population (Female): The female population in the Reading town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Reading town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Reading town Population by Gender. You can refer the same here

According to the results of an early 2024 survey, ** percent of all book readers had read between one and five books in 2024. Consumers aged 65 and above were the most frequent readers, with ** percent having read ** books or more in the last year.

E-Z Pass readers are installed throughout NYC to determine traffic speed on a local street. This creates studies for Midtown in Motion (MIM) projects and other traffic calming and reorganizations to best adjust to the driver's needs. Data is in CSV format and refresh every 5 minutes.

About this dataset

Context

The dataset tabulates the population of Reading town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Reading town. The dataset can be utilized to understand the population distribution of Reading town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Reading town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Reading town.

Key observations

Largest age group (population): Male # 60-64 years (98) | Female # 60-64 years (120). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Reading town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Reading town is shown in the following column.
• Population (Female): The female population in the Reading town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Reading town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Reading town Population by Gender. You can refer the same here

Estimated average scores of 15-year-old students, reading, mathematics and science, Programme for International Student Assessment (PISA), Canada, provinces and participating countries, Council of Ministers of Education Canada (CMEC). This table is included in Section C: Elementary-secondary education: Student achievement of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Graph and download economic data for Unemployment Rate in Reading, PA (MSA) (READ742URN) from Jan 1990 to Jun 2025 about Reading, PA, unemployment, rate, and USA.

This dataset is an extensive eye tracking dataset of 102 participants reading three Dutch literary short stories each (7790 words per participant). The preprocessed data set includes (1) Fixation report (fixation-level), (2) Saccade report, (3) Interest Area report (word-level), (4) Trial report (aggregated data for each page; stories were split up into 30 pages each), (5) Sample report (the data were sampled at 500 Hz, this report includes data on all individual samples), (6) Questionnaire data on reading experiences and other participant characteristics, and (7) word characteristics for all words in the stories (with the potential of calculating additional word characteristics).The study for which this data set was collected explored the effect of simulation on reading behavior by means of eye tracking. We hypothesized (A) that simulation would lead to longer fixation times for parts of the text high in simulation-eliciting content. Additionally, we hypothesized (B) that we would find personal preferences in the reaction to different types of simulation-eliciting content. We expected (C) that the findings from the eye tracking data would be related to self-report of simulation. Finally, we expected (D) that the amount of simulation would be predictive of self-report of appreciation. We found (A) longer reading times for perceptual and mental event simulation, but shorter reading times for motor simulation. The strength of the relationship between simulation and reading times varied between participants, but was positively correlated across the different types of simulation-eliciting content (B). Regarding (C) and (D), we found that this variation in the strength of the relationship between simulation and reading times was indeed related to aspects of self-reported simulation, absorption and appreciation.The findings from this study are described in detail in Mak & Willems (2019). https://doi.org/10.1080/23273798.2018.1552007

The E-Reader Market is Segmented by Screen Size (below 6 Inch, 6-8 Inch, and More Than 8 Inch), by Geography (North America (United States and Canada), Europe (United Kingdom, Germany, France, and Other Countries), Asia Pacific (China, Japan, India, South Korea, and Other Countries), Latin America, Middle East, and Africa). The Market Sizes and Forecasts are Provided in Terms of Value USD for all the Above Segments.

Financial overview and grant giving statistics of Reader-Writer

About this dataset

Context

The dataset tabulates the population of Reading by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Reading. The dataset can be utilized to understand the population distribution of Reading by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Reading. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Reading.

Key observations

Largest age group (population): Male # 0-4 years (89) | Female # 5-9 years (86). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Reading population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Reading is shown in the following column.
• Population (Female): The female population in the Reading is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Reading for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Reading Population by Gender. You can refer the same here

All In One Card Reader Market Outlook

The global all-in-one card reader market size is set to witness significant growth over the forecast period from 2024 to 2032, driven by a robust CAGR of 7.5%. In 2023, the market was valued at approximately USD 1.2 billion, and it is projected to reach around USD 2.4 billion by 2032. Key growth factors include the rising adoption of digital storage solutions, increasing usage of smart devices, and the growing demand for efficient data transfer and storage solutions across various sectors.

The surge in digital content creation and the need for high-speed data transfer solutions are primary growth drivers for the all-in-one card reader market. With the proliferation of high-resolution imaging devices such as DSLR cameras, drones, and smartphones, the requirement for reliable and versatile card readers has become more pronounced. These devices facilitate the quick and efficient transfer of large files, making them indispensable for photographers, videographers, and content creators. Additionally, the growing trend of cloud computing and data backup solutions further propels the demand for card readers as they offer a convenient way to transfer data to and from cloud storage services.

Technological advancements in the design and functionality of card readers have significantly contributed to market growth. Modern all-in-one card readers come equipped with features such as USB 3.0/3.1 connectivity, wireless capabilities, and multi-format support, enhancing their utility and user experience. The integration of advanced security features to protect data during transfer and storage has also been a crucial factor driving market adoption. Furthermore, the miniaturization of card reader devices, allowing for more portable and user-friendly designs, has broadened their application scope across various sectors.

The rise in e-commerce and online retailing has facilitated greater accessibility to a wide range of card reader products. Consumers can now easily compare different models and brands online, driving competition and innovation within the market. In addition to this, the increasing number of small and medium-sized enterprises (SMEs) adopting digital solutions for their operations has bolstered the demand for card readers. These enterprises require efficient tools for data management and transfer, which card readers provide, thereby fueling market growth.

The introduction of Bus Card Reader technology has further diversified the applications of card readers in the market. These readers are specifically designed to facilitate secure and efficient transactions in public transportation systems. By enabling quick and contactless fare collection, Bus Card Readers enhance the convenience and speed of public transit operations. The growing adoption of smart city initiatives and the increasing need for efficient urban mobility solutions have driven the demand for such specialized card readers. As cities continue to invest in digital infrastructure, Bus Card Readers are expected to play a crucial role in modernizing public transportation systems and improving commuter experiences.

Regionally, North America holds a significant share in the all-in-one card reader market, driven by the high adoption rate of digital storage solutions and advanced electronic devices. The presence of major technology companies and a highly digitized consumer base further support market growth in this region. Following North America, the Asia Pacific region is expected to exhibit the fastest growth during the forecast period, owing to the rapid digital transformation, increasing disposable incomes, and expanding consumer electronics market in countries like China, India, and Japan.

Product Type Analysis

The all-in-one card reader market can be segmented by product type into USB Card Readers, Wireless Card Readers, and Multi-Card Readers. Each of these segments caters to specific user needs and market demands, contributing to the overall growth of the industry. USB Card Readers are among the most commonly used due to their ease of use and widespread compatibility with various devices. These readers connect directly to computers or other electronic devices via a USB port, making them a popular choice for both personal and professional use. The adoption of USB 3.0 and USB-C technologies has further enhanced the performance of these card readers, providing faster data transfer speeds and improved user experience.

ABSTRACT Purpose: the study aims to obtain preliminary normative data for early reading and writing skills of 5-year-old children in a sample from the Northeast of Brazil. It also aims to investigate the effects of the type of school (public vs. private) and the time of assessment (beginning vs. end of the school year), and whether there were significant differences in performance, as compared to those of children from the Southeast of Brazil. Methods: 389 5-year-old children from 17 private and 12 public schools were assessed in the beginning and at the end of the school year, by using the Reading and Writing Test. Each student was individually assessed in the two times of the year. Appropriate statistical tests were applied, adopting a significance level lower than 0.05. Results: the progress in the performance of private school children was stronger than that of their peers from public schools, accentuating the existing learning gap. The comparison with normative data from the Southeast revealed that the public schools in the Northeast outperformed those in all topics of comparison. Private schools in the Southeast had a better performance at the beginning of the year, but were outperformed by those of the Northeast at the end of the year. Conclusion: the differences in performance identified in the samples suggest the need for specific norms by geographical regions of Brazil, and by type of school (public or private). The data presented in this study are preliminary and can be enlarged in future studies.